Legalcomplex

We discovered our first legal agent on the first of November. First of December, we counted 559. What are Agents, and what can they do?

TLDR: Legal content is perfectly structured to assist Legal Agents. Legal Agents became possible by GPT fixing many of the downstream issues. Now there are three more obstacles on the road to Autonomy.    

Intro: This is our first-ever double header. The previous one was a bit dark, and we want to end the year on a bright note.

Ante

Before we throw any numbers at you, a bit of context. We covered a similar eruption of new apps twice before. In 2016, we recorded 44 new companies in a couple of months. We called it the Hottest Summer. During the crypto craze of 2018, we found 55 ‘legal tech’ companies raising a Billion in coin. Back in 2015, ProductHunt report, we uncovered a growth of 43 apps in roughly the same amount of days. In the early days of the Apple App Store, we noticed a similar growth. But nothing quite like this.

We were warned four months ago when we found 81 apps in 28 days. 550+ new solutions in one month set a new record. Now, will these new interfaces all be displacing current legal solutions and services? Not yet, and we’ll explain when this displacement will happen. These new apps will face similar struggles as the App Store, and ProductHunt platform posed. However, now there are different market conditions. In “Data, Distribution & Deals” we discussed market conditions that affect supply. This analysis will explore the demand side. Why do we need agents, and are they better?

Ancestors

In order to answer, here is a brief history of how we got here. We first discussed agents in 2011: Call My Agent. Basically, we wanted systems to learn from our content, derive instructions and tasks, and complete these tasks. They could perform their tasks autonomously in the background. This would allow us to access the results instantly at runtime.

In 2013, we created Loupe as a concept that would track regulations and instantly update affected contracts or briefs remotely. You would need a dashboard (DESH) to keep track of all edits deployed on each document. We even made an Apple Watch interface.

The same principle applies to legal research. We could dynamically convert phrases in documents to background queries. That was called Monocle and even made a teaser video. We submitted eleven patent proposals. Little did I know that each submission costs a fortune. Only one was patented, making me an inventor.

Why did we bring this up? Cooking these concepts in the lab, we discovered a few fundamentals of legal work. First, autonomous legal research is about anticipating legal issues, and calculating them beforehand. Second, the legal issues are already present in legal content. You just need to add the right context, as shown in the image above. In short: legal data already has the instructions and tasks baked in.

The biggest problem back then is actually what everyone now knows: calculating has immense costs. The OpenAI breakthrough is that no one has to pay that much. By creating GPT, OpenAI has democratized Legal Agents. Give GPT the right legal data, and anyone can create a Legal Agent.

Agents

What is a Legal Agent? Based on a given context, a legal agent can serve up a legal end-product like a contract, or research brief. If you ask GPT, it will provide a more technical answer. Something like “entities that can perceive their environment through sensors and act upon that environment using actuators. They’re designed to achieve specific goals or perform certain tasks.”. Not helpful, except it does provide the key ingredient for agents to work: context. Legal Agents get Legal context from instructions and legal data.

Before GenAI, every legal technology solution had to derive context from the user manually. As a Legal Knowledge Engineer, I had built legal decision trees and the process was very tedious. The tools were cumbersome and we could never encompass all cases. We just focused on the most complicated ones for commercial purposes. Now, with the right instructions, and a fined-tuned model can figure it out. Better yet, you can ask to explain the answer. This was the real breakthrough of TaxGPT. So are we there yet? Not yet. Let’s highlight one key difference we uncovered while covering GPTs: Copilots answer your questions, Agents take actions. So what is the next stage?

Autonomy

The launch of GTPs on November 6, 2023, made instructions more explicit for ChatGPT. However, OpenAI demoed instructions months earlier on March 14th, 2023. Remember TaxGPT? Yes, the first agent by OpenAI was targeted at Tax. Now there are around 90 TaxGPTs and counting. However, none can submit a tax form to your local IRS. While the current generations of legal agents can give you perfect answers, most can not take any action. Part of this constraint is security by design. Large Language Models will prevent any kind of code execution outside a sandbox. However, developers, that have APIs for actions ready in their apps, can now use GPT output as input. As the Copilot Battle states, this is the footrace, so hurry. Wait! There is one more thing.

Besides structured legal issues, we made one more discovery in our Ancestor era. A quick step back: The best definition of Artificial Intelligence I heard here at 4:59 min on the Waveform Podcast. The short version: AI is planning tasks in the right order to execute them. Sticking with the TaxGPT, here is a simple plan:

1. Upload your bookkeeping*;
2. Classify entries;
3. Find the right deductions;
4. Fill out the tax form and;
5. Submit tax form to Tax Office.

*Note: Another Agent did my bookkeeping.

What tax and legal data provide is an understanding of how to structure tasks and actions to solve legal problems. Legal data has a complete recipe. Given this recipe and the ability to take action, Agents will be able to act autonomously. So the next stage of legal solutions is autonomy. And now you know why Sam was fired.

Agree

On the roadmap to autonomy, we have to travel through the Three Universes from “Will lawyers be replaced by GPT” which are:

1. All legal data needs to be processed in GPTs. As stated in the previous post, it eventually will;
2. Learn how to construct Agents to allow them to safely take actions, so allow autonomy;
3. Interceptors do not squeeze developers, so allow fair competition;

This third milestone is, economically, the most difficult one because of Interceptors. Example: Google Bard now supports extensions and they are all Google apps. OpenAI was supposed to be open, but now it’s just Microsoft Copilot. Ideally, GPT becomes an open utility, just like GPS. Politically, it seems we are beyond that possibility. Potentially, agents can save the world, if we agree we want them to.

Meanwhile, we counted over 24,000 GPTs created since November 6th. That is 750 GTPs a day.

Around $40 Billion of business supporting legal relies on copyrights, complexities, and expensive distribution. Now that’s all in jeopardy.

TLDR: This is twice our usual length, so if you’re in a hurry, skip to the Recaps and Daybreak.

Premise: Any business needs a model for making money. A tech company model is to use software to solve problems and then sell this solution with a profit. The problems in legal usually involve complexity. So the business models for legal involved finding and fixing complexities. Now, this is tricky: Finding complexities in legal with tech is very lucrative. Fixing them, not so much. Well, guess what happened?

Data

Based on 2022 annual revenue, the three biggest companies supporting legal work arguably are:

1. RELX (owner of LexisNexis) – $8.55 Billion;
2. Thomson Reuters (TR) – $6.63 Billion;
3. Wolters Kluwer (WK) – $5.45 Billion.

That is $20.6 Billion of revenue for 2022. They did not achieve this staggering feat overnight. Each company was founded in the late 1800s. They achieved gradual growth by accumulating essential legal content. Two key factors drove their model: Copyright on content and competency requirements for legal professionals. In essence, they monopolize the data that lawyers need. Eventually, RELX, TR, and WK diversified their product portfolio away from legal. Yet, the legal market made this model sustainable for over a century.

Historically, distributing legal data was expensive because it required printing on paper. The printing press was owned by publishers and allowed the monopoly. Lawyers also have a monopoly on legal work, which allows them to maintain complexities. For these reasons, the legal industry could keep raising prices and making profits. This flywheel effect resulted in ‘legal inflation‘ and years of wealth in the legal market.

Recap: Picks & shovels for legal brought in $20 billion annually. It took the incumbents centuries to grow profits. Those profits are protected by copyright and the monopoly lawyers have on legal work. 

Distribution

Non-Legal Data

With the internet and cloud, the distribution of legal data got cheaper. More legal professionals got smarter research portals and e-Discovery platforms for non-legal data. In particular, e-Discovery platforms managed enough revenue growth to go public. Here is a list of the ones we’re tracking:

1. Open Text – $3.49 Billion;
2. Palantir – $1.91 Billion;
3. KLDiscovery – $317.43 Million.
4. Information Services Group – $286.27 Million;
5. Intapp – $272.07 Million;
6. Model N – $219.06 Million;
7. Nuix – $152.31 Million;
8. CS Disco – $135.19 Million;
9. Fronteo – $73.17 Million;

That is $6.8 Billion of revenue for 2022 and remember that their revenue streams are also diversified. Why e-Discovery is the biggest cohort is due to a craze, we experienced in the early 2000. The Exit and Funding videos show this historic rise and fall in graphic detail. We’ll spare you the legal drama some encountered during their public run. Same for the earnings per share (EPS), an indicator of profitability.

Other Legal Data

Primary legal data monopolies prompted others to search for secondary legal data. They focused on areas like Practice, IP, Billing, and Government. Here are some we track that support legal professionals:

1. Constellation Software – $6.62 Billion;
2. Dye & Durham – $474.81 Million;
3. PEXA – $279.84 Million;
4. Clarivate – $2.66 Billion;
5. Upland Software – $317.30 Million;
6. FiscalNote – $113.77 Million.

That is $10.4 Billion of revenue for 2022 and about 60% goes to Constellation. Bear in mind, that Constellation has a bunch of businesses under their umbrella. So pure legal is a considerably smaller piece of this revenue pie. PEXA deals in real estate legal transactions.

Other Legal Stuff

Most of the models above rely on catering to legal professionals. Hence, they have slow but steady growth. Now, newer models offer faster growth. To achieve fast growth, you need a faster deal flow. Faster deals happen when you can cut out the middlemen. Therefore, these models did not sell directly to the profession, they sold to the business. Marketplaces, Tax, Cookies, and e-Signature were designed as a direct-to-legal-consumer business. Their model used the ‘land & expand’ method for growth. Here’s a list:

1. Docusign – $2.11 Billion;
2. LegalZoom – $619.98 Million.

That’s $2.7 Billion. All of the above is $40+ Billion in revenue for 2022, and we would be generous to say it is all legal. All links go to Google Finance so you can check, and track it yourself. Most stocks are trading way below their initial public offering. Meaning, they are not doing as well as expected. Hopefully, by the time you read this, they’re doing better.

Will there be more? We’re tracking about, 1033 private companies. They have raised more than $20 Million in total from investors. In June 2022, Clio announced it had reached $100 Million in annual revenue. Based on our calculation, Clio is not the only ‘Centaur’. We see a couple doing Tax or Cookies that should be near $100 million. Nope, Contract Tech isn’t there yet. Unfortunately, their outlook is not rosy either. Check out Deals and Daybreak to see why.

After decades of ‘innovation’, and about $118.58 Billion invested, just seventeen joined the traditional three. In any case, the rest have three options: raise again, get acquired, or go public. They can stay private forever if they have profits. Profits come from growth and growth comes from Deals. So what about Deals?

Recap: Out of the 11,000+ ideas, just 17 went public. The seventeen made $20 Billion in revenue combined, which is as much as the traditional three. 

Deals

We did not include a list of publicly traded law firms, Reg Tech, and Tax Tech. Most law firms are doing well. How well? Twitter’s M&A lawyers effectively charged $122K an hour. While this may seem excessive, it represents just 0.2% of the $44 billion price tag paid by Elon Musk. These deals rely on connections or an effective M&A prospecting tool. In Capital & Conflicts, we addressed dynamics that drive deals in legal. Those dynamics were driven by the demand for legal solutions. Now, we have a supply issue. Specifically, an oversupply of legal solutions, and here is the cause.

First, large language models (LLM) will break data monopolies. Meaning, that all data will eventually disappear in a LLM. Most hope for some kind of copyright or regulatory arrangement. Well, search engines ignore copyright and cookie policies basically broke the web. Note Sarah Silverman’s AI copyright infringement lawsuit against Meta stumbled. In general, monopolies do not work well for consumers. Moreover, the main LLM providers offer a copyright shield. So regulation will be futile. This brings us to our second and bigger concern.

We enjoyed cheap internet and cloud to distribute our solutions to customers. Now we’re getting these expensive chip clusters to run LLM’s. Before, we only needed to write code and distribute it. Copilots are different. The biggest shift is that generative pre-trained transformers (GPT) will intercept most end-user interactions. There are only three Interceptors currently capable: Google, Microsoft, and Apple. They have the chips, brains, and devices to capture all questions. And they will monetize it, too. Due to these additional costs, legal solutions become more expensive. This will further dampen demand and deals. This decrease in demand and increase in supply is a perfect storm.

Recap: The costs of creating a legal product that uses GenAI are now unpredictable. However, GenAI will solve the majority of the legal problems they process. The oversupply of legal solutions will drive down demand and deals in the legal market.  

Daybreak

In 2020, we wrote, “Will lawyers be replaced by GPT? Yes“. Wonder why Sam was fired from OpenAI? Read the second sentence in ‘Universe Three‘ from the analysis. Well, if we saw that coming, here’s what we see next:

• Transformers will vaporize copyrighted data monopolies;
• GenAI will fix most legal issues they intercept;
• Interception will not come as cheap as code and cloud;

Curious, who is eagerly funding Interceptions? Investors made their VC Legal Copilot so they may not be allies. GenAI is the new printing press, and no legal tech company owns a printer. That is why we called the Casetext acquisition a bargain. To protect $6.6 Billion in revenue, a $650 Million investment (9.8%) is reasonable. Not realistic but reasonable.

In short, that $40 Billion revenue above is in jeopardy. Legal business models relied on a monopoly of middlemen. Now, the middlemen have a new master. This master has shown us some new tools and tactics. That's why we wrote this bonus below.

What Are Legal Agents, And The Next Stages Of Legal Services

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Image Courtesy: DALL·E 3 by OpenAI based on the content of this analysis.

In the midst of this credit crunch, there is a candy store of capital called Private Equity. What does this mean for the legal industry?

TLDR: Venture Capital (VC) focuses on supporting early-stage or high-growth companies. Hence, a dip in growth means a drop in VC funding. To stay afloat, legal tech companies as well as law firms turn to private equity or debt funding. The catch? A shift in power from founders to private equity analysts.

Private

Private Equity (PE) involves investing in mostly privately held companies, rather than publicly traded ones. PE firms raise capital from institutional investors, such as pension funds, endowments, and high-net-worth individuals. The goal is to generate significant returns over a specific period. In order to achieve this goal, a PE firm will often take control. They need to drive growth and increase the value of their investments. Obviously, who doesn’t, so what’s the worry?

Any copilot can explain what the PE model is. We offer you a specific calculation of why we wanted to know. Since 2020, we counted an uptick in companies raising through debt financing or private equity. In 2021, it drove us to discuss the difficulties of debt. The Q3 2023 post, elaborated on differences with venture fundraising.

What did the calculations reveal? As of January 2022, we tracked $1.5 Trillion in capital raised by investment firms for various reasons. In our June ’22 report, it was still just $50 Billion. Moving the slider above left will reveal how much money went to PE firms (66%). That translates to over a trillion raised in just 277 PE deals out of over 1,200 deals. How crazy is this stat? On average, this is $1.7 billion a day. This is not just power, this is concentrated power. Now, how does this power present itself?

Power

All of the above made us wonder: In these difficult times, how can PE firms raise so much? They are able to offer better returns. How is this possible? Well, we have to explain the most peculiar trick these financial instruments employ: Leveraged Buyouts (LBO’s). In LBO’s, companies are acquired using a combination of equity capital and loans.

Imagine a private equity firm wants to acquire a company valued at $100 million. When a firm uses an LBO, it might use $30 million of its own capital and borrow $70 million to cover the total cost.

Now, let’s say the private equity firm improves the company, and a few years later, it’s able to sell it for $150 million. Subsequently, the firm repays the $70 million of borrowed money, and the remaining $80 million is their profit. Now, look at the return on their own invested capital: They invested $30 million and got back $80 million, which is almost 3x their investment.

Why would a PE firm not use its own capital to fund an acquisition? If the firm had used all its own capital to acquire the company (i.e., $100 million), a sale price of $150 million would still give them a profit of $50 million. However, the return on their invested capital would be 50%. In this case, the return on investment is just 0.5x.

By using debt, the private equity firm magnified its return on invested capital, even though the company’s total value increased by the same amount in both scenarios. This is why leveraged buyouts are more profitable.

Still confused? We left out the key part of this strategy: The debt acquired to purchase the company is then placed on the company’s balance sheet. This makes the company responsible for repaying the $70 million loan. The private equity firm’s capital remains mostly intact and can be used for other investments or acquisitions. Isn’t that sweet.

Pressure

Let’s recap: If companies need outside capital to operate, there is a giant pile of cash called Private Equity. Specifically, getting access to it requires giving up control. To ensure PE firms get their return, they will exert pressure to increase the value of the company. When there is little growth, the value can only increase by raising prices and cutting costs. The fastest shortcut is cutting staff. The hardest staff to cut is sales and core operations. Everyone else is expendable, including founders. If you have been following legal tech, you have seen this play out in several companies.

Perhaps you are wondering: Who’s the sugar daddy? In order to find out, we had to rebuild parts of our datasets. SQL gymnastic aside, complicating matters is that one company can have a mixed bag of grants, VC, and PE capital. Here’s what we found: 951 investors in 281 deals in legal tech and law firms. Surprisingly, neither Insight Partners nor HG but K1 is the most active Private Equity investor in Legal, according to Spark Match. Better yet, if ranked by participation, TA Associates bubbles to the top.

Sticking to our policy on private companies, we don’t name them in our analysis. However, we did share that public companies, like Legalzoom, hold the largest loans. Note that law firms in the UK can be listed as public companies. Law firms taking loans isn’t new, yet we also found a few that raise venture capital. Previously, we only registered tech companies having access to VCs. A sad side effect: These nuances are causing us to lose friends. These numbers don’t fit their narratives. Especially, narratives indirectly made possible by…private equity.

In closing: Our worry isn’t just pressure on the bottom line, as stated in our previous post. It is the fact that founders of legal ventures are losing control. We are at an inflection point in the history of the legal industry. For over 5,000 years, legal counsels have been the engineers of a safe society. This is the worst time for legal to lose their independence.

The way to wrestle back control is to know. Know where to get capital to survive. Know where to find customers to thrive. Schedule a chat.

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**updated Oct 27, 2023 – 15:01: LBO equity checks top 50% for the first time, thanks to high interest rates – Axios**

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Editor’s note: The analysis uses Legalcomplex Spark data to artificially generate parts of it.
Image Courtesy: DALL·E 3 by OpenAI based on the content of this analysis.
Copyright notice: Your © guess is as good as mine.

What were the Q3 2023 results, and what is the current market climate? How is AI impacting the Legal Tech industry?

TLDR: Legal Funding in Q3 2023 is normalizing, with Europe surpassing North America in capital raised for Legal Tech. AI’s impact is more evident in consumer-focused companies.

Housekeeping: we skipped our September analysis, but we had a good reason. That is why you’re getting a double shot this October. We’re also generating our analysis with GenAI. Basically, we’re feeding the machine our stats and teaching it our style.

Ok, curious about this year’s Legal Funding and M&A activity compared to 2022? Did you see our input on Law360’s analysis? Then let’s dive right in.

Legal Funding Q3 2023

1 Legal Funding for Q3 2023 stood at $590 Million, a 26% decrease. Deals numbered 85, marking a 11% drop. Interestingly, the number of investors plummeted by 45% to 145. These numbers do not include Governance, Risk, and Compliance (GRC). If we did include GRC, the total would be $4.8 Billion, and it would still be down 26% from last year.

Now, what’s Legalzoom doing up there? Aren’t they a publicly traded company? Yes, but they did raise privately. Just like law firms are also raising capital on private markets. Since this train has been picking up steam, we are keeping track. Why? Keep reading…

Debt vs. Venture Funding

2 If we ignore 2021 and 2022, the 2023 funding numbers look in line with expectations. However, if we look at the types of funding, we see a pattern emerging. Debt funding for the quarter was $243 Million, 41% of the total. Over the past year, debt funding reached $2.18 Billion (image above). Venture funding was $1.52 Billion in the last 365 days, but is significantly less by comparison. Remember, we discussed the burden of debt all the way back in 2021. That is the year we registered a record $2.6 Billion of debt raised by legal ventures.

What does Debt tell us?

3 It’s essential to clarify our funding classifications. Anything not labeled as venture or seed is considered debt. This includes equity financing, which technically isn’t debt. Why? To determine two scenarios: a company’s stage and a market’s climate. These metrics tell us: are we early, thriving, or merely surviving?

• Seed and Early-stage Funding: Companies lack a product-market fit. It’s too early to judge them because they have yet to bloom.
• Series and Venture Funding: These companies have revenue, yet they burn capital. Therefore, companies need to raise for rapid growth, indicating a thriving stage.
• Private Equity or Debt: These companies need cash and can’t secure venture funding. They go into survival mode when growth stalls.

Except for grants, the financing options mentioned involve borrowing against the future. There is no such thing as free money. Nonetheless, Seed and Series funding are luxuries, while Debt is a necessity.

Exits & Geography

4 Exits totaled $5.39 Billion, down by a whopping 68%. Notably, Magnet Forensics led the exit deals, not CaseText. The number of exit deals was 76, a 30% decrease.

If we looked at where capital was raised, Europe, including Great Britain, outshone North America. EU plus GB raised $1.16 Billion in 2023, while North America secured $1.01 Billion. We can not recall this ever happening.

Areas of Growth

5 Excluding Tax, the top categories that raised capital were: Practice Management (30%), Contracts (13%), and Claims (13%). AI did not necessarily turn a company into a desirable object for investors. To the contrary, we have yet to figure out the true costs of copilots. AI’s influence is in creating new products with a much broader reach. That’s what we discovered after capturing 81 new companies in just 28 days. In total, we added 1549 companies plus 18 new cities in a 333-day timespan on Legalpioneer.org. As explained at the 4th annual Global Legal Forum, these companies were not all founded recently.

What are the Patterns?

In case you missed our inaugural event, these were some of the revelations. To recap:

• Legal funding is back to realistic levels;
• Better yet, early stage companies have access to more capital;
• The worry is revenue growth is stalling, and it has been since 2021;
• By creating new products, Legal may find new revenue.

Listen to The Equity pod where Crunchbase explains the word: realistic (hint: context is everything). If you did listen to the pod, you’ll hear some deviating results. For example, that seed funding is down. In the context of legal startups, the opposite is true. This historic fact, we revealed to the University of Leiden 11 months ago. Contrary to later stages, young companies are yet “too early to judge”.

Who is being judged? Stalling growth is currently most noticeable with Legal Tech stocks. Remember, the legal numbers above do not include GRC. Which may explain the legal tech stocks outliers (again: context). In short, the legal space is more nuanced than others would like you to believe. So what are others saying?

• 25% increase in caseload due to better Practice Management by Clio;
• 64% of in-house legal counsel haven’t used AI for legal work by ALM.com;
• Wheels Of Justice Slow To Accept Legal Tech As Funding Falls by Crunchbase;
• The Q3 venture capital market explained in five charts by Techcrunch;
• Global Venture Funding In Q3 2023 Falls Again Despite Late-Stage Rebound Led By Huge AI Deals by Crunchbase;
• VC continues to stumble through 2023 by PitchBook.

In short, we do our own homework. If you value context around numbers. If you need to know, what it all means for your area of operations. Schedule a chat.

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Note: This analysis is partially artificially generated using numbers and calculations captured by Legalcomplex Spark.

I wrote these down to build courage and confidence. Here are five insights on how I try to transform rejection into traction.

1. Rejection is Feedback, Not Failure

Every “no” you encounter offers a chance to refine your approach. However, it’s also essential to remember that sometimes you might be right, and the rejection might be wrong. Instead of solely viewing rejection as a failure, see it as feedback. Perhaps your pitch didn’t resonate with a particular audience, or maybe your product needs adjustments. Embrace rejection as an opportunity to learn, but also trust your instincts and the value of your proposition.

2. Persistence is a Superpower

Some of the most iconic entrepreneurs faced a barrage of rejections before their ideas found their footing. Howard Schultz, the visionary behind Starbucks, was rebuffed by banks 242 times. Prepare to receive refusals from both capitalists and customers. The entrepreneurial path is rife with highs and lows. Patience and persistence are inseparable allies. Each rejection is a stepping stone, underscoring that success often demands both time and tenacity.

3. Diversify Your Approach

If one avenue seems blocked, it’s time to explore another. Build a targeted investors list that hasn’t invested in your market but understands your business and aligns with your personality. This not only elevates your chances of finding a receptive audience but also enriches your understanding of your product’s versatility. Moreover, having alternative financing options, such as debt or grants, can build resilience, ensuring you’re not solely reliant on one funding avenue.

4. Emotional Resilience

As an entrepreneur, safeguarding your emotional well-being is paramount. While rejections can be disheartening, it’s vital to disentangle personal feelings from business outcomes. Empathy, understanding others’ perspectives, and seeking mentorship can be invaluable. Remember, rejection doesn’t diminish your worth; it often signals that certain elements need recalibration. And while these challenges can be daunting, it’s essential to maintain perspective; these are challenges of privilege and not matters of life and death.

5. Celebrate the Opportunity

Amidst rejection, it’s tempting to overlook the very opportunity to pitch. Regardless of its outcome, every pitch, is a chance to share your vision. Celebrate these moments as wins, for they signify progress and the continuous journey of entrepreneurship.

In conclusion, rejection, while discouraging, is an integral facet of the entrepreneurial journey. By confronting it with patience, understanding, and a proactive mindset, entrepreneurs can metamorphose these setbacks into stepping stones. As the adage goes, “Success is not final, failure is not fatal: It is the courage to continue that counts.”

I’m curious: how do you overcome rejection? Happy to hear your thoughts.

Understanding the Casetext deal requires us to take a helicopter view of the landscape. We’ll need both a copilot and a landing pad.

Solo

A startup with only one employee and no outside funding sells for $54 million. Wargraphs was founded 10 years ago, and the reported revenue last fiscal year was $12.3 million. If you don’t have ten years, consider the following. Enter Dumb Money, the story behind Roaring Kitty and GameStop. Roaring Kitty reportedly made $20 million within four months betting against short sellers. Now what do Wargraphs, Roaring Kitty, and Legalcomplex have in common? Despite the different markets and outcome, it’s a single person behind a single PC doing data analytics.

The theory that it takes an army to build a profitable company is slowly being debunked. The underlying idea of technology is to leverage it as a tool. Even though these tools are getting more powerful, they’re also becoming more affordable. And now every company is looking at their human capital and wondering, how much do we actually need? If you’re in one of these companies, I empathize but remember: you are free to fly solo. You may only need a copilot.

Copilot

This brings us to the reason you’re here: Casetext will be acquired for a staggering $650 million by Thomson Reuters (TR). By the way, Casetext was the second acquisition by TR in the week the deal was announced. Imagen was bought at a 1.9x return. A company we’ve been tracking since 2019. So there is a bigger picture, we’ve yet to see. Pencil this date into your calendar: Wednesday, 2 August 2023, and join us at the Q2 earnings call. In Supercycle, we explained why we sit in on calls.

Now let’s proceed by answering two questions:

• Why now?
• And is it too much?

We classify Casetext as ‘Legal Research’. According to the TC article, they eventually morphed into more than just search & retrieval of legal data. Now one can use a Generative Pretrained Transformer (GPT) to search, retrieve, analyze, and draft texts all at once. Hence, many refer to this as “generative AI”. Unfortunately, we’re allergic to the term AI. Yes, we’re taking pills and eventually, the sneezing (bullsh*t) will stop. Instead, we use the term ‘Text Analytics’ because it highlights the key additional capabilities: recognition and analysis.

Based on the reasoning above, we classify companies as follows:

• Text Analytics;
• Data Analytics (which can also handle numbers and calculations);
• Audio Recognition;
• Image Recognition.

Transformers take the data inputs above and transform them into drafts, drawings, or any format fit for human consumption. Actually, transformers are much better at providing computer code than human content. They essentially generate food for bots. We endearingly call these bots ‘copilots’, and every industry will have many flavors. For programmers, content writers, doctors, and legal professionals. Ultimately, transformers opened the floodgates for anyone to build copilots. So now we’re all in a footrace to distribute them. Hmm, distribution.

Sky

This brings us to $650 Million, and we ran this through GPT using multiples and DCF calculations. Most came back with unrealistic assumptions of revenues and returns. So here’s a simple angle: Casetext raised $64 million from investors and is acquired for ten times that amount. That is 10x return in ten years, resulting in a 29.2% CAGR. The investors get 10 times the invested $64 Million. Here’s where we’re going with this: what does Thompson Reuters expect to get in return?

If Thomson Reuters paid 10 times, logically, they should expect to gain at the same rate of return. This means by 2033, they should expect to earn $6.5 Billion from this investment. This logic only connects if the growth of paying customers remains at or above a 29.2% CAGR in the coming ten years. Now this gives us something to look for by August 2024 earnings season. We love to know: will demand grow?

Since consumers will get most copilots for free, professionals will likely want the premium stuff. Sophisticated users desire solutions that offer a complete package. This means that when we offer a pilot, the pros will also want a plane and an airstrip for takeoff. In short: building the infrastructure for pilots to thrive doesn’t come cheap. From that perspective, the value makes sense. In fact, the deal may even be a bargain. Heck, everyone will want to fly private eventually. Therefore, we aren’t worried about demand nor supply. However, what about distribution?

Cockpit

To circle back to my GPT-4 factor question on LinkedIn: it was a rhetorical one. OpenAI owns GPT, and Microsoft paid $11 Billion to push it onto every lawyer’s cockpit. Google, has a $1.5 Trillion market cap and arguably the deepest bench of AI brains. And they still haven’t caught up. So, becoming the Legal Copilot with just $650 million might be a brilliant move ten years from now. Note: Thomson Reuters had $1.3 Billion in free cash flow by the end of 2022. So it’s not like they broke the bank to broker this deal. They’ve been pretty quiet on M&A up until now.

Still, it leaves us wondering one thing: why didn’t Thomson Reuters go directly to OpenAI? FiscalNote did, and if you’re curious about how that turned out, watch their video on our TV channel. Stick around for the second video, showing us another interesting pilot. Sadly, that plane disappeared from our radar. After you’ve watched the video, you’ll understand why it may have been shot out of the sky.

I hope you had a pleasant flight, and a special thanks to our flight crew:

https://www.youtube.com/watch?list=PLMFkDqsbOzZ4dKVt-HL9J-MH5wPHtwT7W&v=tJYI3ehqTmo

Marc Benioff from Salesforce calls this moment in time a supercycle. While, the reports are mixed, the reasons remain remarkably subtle.

Mass

For those new to Legalcomplex: we missed our analysis in May, so this one includes June as well. We presented numbers at Futurelaw 2023 in Estonia and were asked to share slides. Meanwhile, Apple unleashed a new computing paradigm and made us nostalgic. Finally, we’ll explain our confusion about DocuSign’s latest earnings. Now, we always limit our posts to three minutes read time. It’s a discipline to suppress any delusions of grandeur. Therefore, this is our most dense analysis ever.

Myths

We presented a couple of spoilers in Tallinn. One slide on the size of the legal market in contrast to GRC or FinTech (Hint: it’s tiny by comparison). A slide about what lawyers and firms want to buy. (Hint: they rather build tech themselves). We delved into Europe and the Baltic Rim but started with AI. We had to because two days prior, Nvidia became a Trillion-dollar company. A reminder that lasting wealth usually ends up with picks and shovels. Next time you wear Levi Strauss, remember to read up on the 1853 gold rush. So, the spoiler? Profits from AI currently come from hardware, not software.

Bewildered? That was just a warm-up. Let’s address three more myths:

1 AI investment is taking off. Investments in AI have been dropping precipitously. In 2022, AI investments plummeted by a 26.7% decrease over 2021 as reported in AI Index Report 2023 by Stanford. Are things looking up this year? Nope, the downward trend continues, as shown in CB Insights AI funding for the first quarter of 2023.

2 AI will return on investment. The fact that investors struggle to find value in AI correlates with the cost of scaling AI. It costs OpenAI $700,000 a day to run GPT. We’re not debating the value. We’re just calculating how quickly it can return on investment. AI will increase efficiency, not profitability. Currently, it’s just too expensive to scale.

3 Legal AI investment is taking off. Surprisingly, it could. Despite macro trends, Legal AI funding held steady. The white line in the chart below reveals no big dips in the last three years. The chart cut-off is May 18th. This is just halfway through Q3, 2023. And this explains the drop at the end. As previously stated: Legal is Stable & Durable.

Mindscraper

So what will Legal AI do? History, tells us that it will expand legal business and profitability. Remember what e-Discovery did for litigation? It allowed law firms to tackle bigger cases with fewer fee-earners. E-Discovery gave lawyers a forklift, so they could now bill for skyscrapers. More revenue with less overhead equals higher profits. This caused a stampede to join the e-Discovery bandwagon. We measured the impact of e-Discovery by several exits in Legal since 2001. See the video below and watch what happens after 2004 up until 2019.

However, after the HP-Autonomy $8.8 Billion bust in 2017, exit options for e-Discovery chilled. Therefore, the only way for the bigger ones was to go public. Now, if you look at stock prices today, and compare them to the initial stock offering. Well, let’s not rub it in and get canceled. We’re sticking to our principles and not name these. Better yet, I’ll offer a message of hope: “Buckle up those jeans, and remember what you are”.

Mixed

This brings us to tell a tale of two legal technologies. Here’s a pro-tip: a shortcut to get a pulse on the legal market, is by listening to earnings calls. The question & answer (Q&A) is the juicy part. Note: the next three links jump to the mentions in the YouTube versions of the calls.

Dropbox narrative has two sides. First, the e-Signature struggle is still real, yet Dropbox did get a bump from Formswift: a legal doc platform. The reason was tax season. While the HelloSign acquisition remains a strategically important asset, it did not contribute as meaningful as Formswift. Neither has Docsend, another Dropbox acquisition. Why? Both HelloSign and Docsend, suffer from a severe drop in deal flow in many industries.

But not all segments suffer the same fate. Two weeks later, DocuSign earnings call comes with an upbeat message on contract tech. Now I’m baffled. However, we noticed a subtle but crucial difference between both calls. During the Q&A, Docusign singled out real estate as weak versus manufacturing and business services as strong. Ask GPT: what are business services? Among a short list is Consultancy, Legal, and Supply Chain. Also known as “Picks & Shovels”.

Bottom line: Dropbox won with Tax and DocuSign relied on Legal and several other ‘shovels’. Only looking at the extremes “Capital & Conflicts” will make you miss everything in between. Kudos to pro analysts on these calls asking questions. They help rookies like us to see when areas in legal deliver profits. So, Legal Tech, whenever you’re ready to harvest, grab a shovel.

Recap: mixed signals will remain since legal relies on seasons. While the tourists only enjoy the summers, the pros can weather any storm.

Any investors would love to see growth with a moat in a startup. Realistic investors know the market conditions for that to happen.

Disclaimer: We co-authored this post with GPT-4 and persona X-Ray. X-Ray is generated with GPT by having it analyze our Study section. We loaded X-Ray with data from Spark Max and added specific expertise to boost cognition in certain areas. It took 102 prompts to get a result, so stick around to hear our thoughts.

Breaking Bad

Funding companies by investors has fallen off a cliff in the first quarter of 2023. Yes, it is bad but, it is not all bad. To illustrate, we created a unique view on investing in Legal. A view that looks at investors in founders. Based on this view, we generated tips for you.

This is a deep cut, so bear with us. Back in 2018, we revealed that the average number of investors per startup in legal was about five per company. Break down this number in mature and young companies, and you’ll see something different. The drop in participating investors isn’t as dramatic as the drop in the amount they invest. Moreover, we see a light increase for young companies. Better yet, fewer investors cut bigger checks at seed stage. How do we know?

The graph shows average investor count (green line) and investment amount (blue bars) for companies in the legal space. The left side shows mature companies receiving later-stage funding. The overlay chart is the same for young companies getting seed-stage funding. Swipe the image between growth and seed and see the difference. Yes, it’s deep but important nonetheless.

Five Unconventional Tips

There is more good news hiding in data and it’s usually counterintuitive. Here are five non-obvious tips:

1. Identify ideal investor;
2. Know your exit;
3. Find better customers;
4. Embrace lean operations;
5. Demonstrate tangible growth.

1 Identify ideal investor

Currently, there are more investors sitting on the sidelines than at any point in human history. Institutional funds globally raised over a billion dollars a day to invest. Almost none of it is being deployed, but eventually, it has to. Remember, middlemen don’t get paid, when deals don’t get done. There is an easy way to identify the investors that match you, and you can surprise them with your pitch. So the steps are:

• Find Customers who would also be willing to be your investors;
• Locate investors Close to you and your principles;
• Identify those with FOMO, who haven’t yet invested in but understand your market.

2 Know your exit

We’re now in a slow economy where two exit options became popular: mergers and acqui-hires. Mergers are a sign of a maturing market with slow to zero growth. Our tip: avoid those areas. This leaves option number two and a possible third. Being snapped up quickly or IPO big in about seven years happens under these conditions:

1. Fast exits happen when you built a feature that is hard to duplicate.
2. Big exits happen when you have a customer base that is hard to replicate

In both cases mentioned above, being flexible and free in your strategy helps. So what does the above average investor graph tell us? Fewer captains make for smoother sailing. If you are bootstrapped or have only one or two investors, the decision to exit is less complex.

3 Find better customers

If you decide to exit big, then current conditions are ideal. If you can grow naturally in a slow economy, you’ll launch like a rocket when things pick up. Natural growth comes from a sticky customer base. Sticky happens when your product is essential. Real sticky happens when your product is required by law. As legal, we serve many essential industries that need to be risk-free and compliant in order for us to trust them. Those industries need trust. Our society requires trust. So what is in very short supply and in hot demand? Trust.

The saying goes: Trust takes years to Build, seconds to break, and forever to Repair. That is how we view the business of legal: building and repairing trust. Yes, most get stuck watching the hourly rates of lawyers and thinking of them as fat wallets. Once you are able to move pass this, you may discover the bigger opportunities for the legal industry. Perhaps the biggest opportunity legal has is to build and repair trust between companies and consumers. It is a way bigger market, making them both better customers.

4 Embrace lean operations

It takes money to make money. Well, get used to the fact that there is no money. Before inflation, companies grew by pouring cheap capital into companies. If you missed the memo, that strategy no longer works. Now, everyone will want to conserve capital while maintaining revenue. Here’s the paradox: everyone will spend less while simultaneously figuring out to let others buy more. Economics force us to do more with less. In one word: Efficiency.

Ingenuity is a free, yet an extremely scarce resource. If we use ingenuity to gain efficiency, the result is usually Automation. Just in case, you also missed the other memo: we can now use this tool called GPT. Ok, I took it to the extreme by making it the co-founder for our new company. I’m just embracing it out of Necessity: the mother of all inventions.

5 Demonstrate tangible growth

This brings us to our final point: will (more) people keep buying? We’ve learned that pre- and post-pandemic provided different answers to this question. In our pod appearance and previous post we indicated that we’ve now entered a new era. This means we’ll discover new metrics to gauge growth across the globe. Despite the fantastic narratives you hear from formidable names, keep listening for numbers. When you hear a number, then watch for these two words: ‘usage’ or ‘adoption’.

Those numbers are notoriously hard to get real about. We use proxies to calculate usage of solutions in any area. We use capital raised, employee growth, traffic stats and even Adwords pricing fluctuations to find out what grows. If this last metric doesn’t make sense, then perhaps you’ve never had to calculate the cost of acquiring a customer. This goes back to another deep cut from 2019: The cost for acquiring a customer in legal is among the highest in the world. Therefore, no need to envy fat wallets. Like we stated in this video with a shrug: illustrating growth is easy, demonstrating is it hard.

Boilerplate

Now, about using GPT-4: it is the best at producing boilerplate. It requires a lot of data and prompting to steer it away from default, which is looking for consensus. If you require something counterintuitive, you’ll need prompt engineering. So GPT gave us a starting framework and inspired us to…scrap its framework and start over. It’s unparalleled in research, but be careful with the facts and examples that it provides. GPT gets you started, but you need to polish it. Lots of polish.

In Hallucinations, we made the case that finding the extraordinary in the ordinary is GPT’s greatest strength. However, it needs our ingenuity and creativity to do it. For most cognitive tasks, humans are in a weight-lifting contest with a forklift. But with a forklift, we can build skyscrapers. So to build skyscrapers, a forklift requires us, humans, to imagine it.

With GPT, we can imagine and build mindscrapers.

I got to meet heroes. In the wake of the disruption the week before, we discussed the opportunities and threats facing the legal industry.

Legalweek

On March 14, 2023, OpenAI released GPT-4 and demoed live at the 19:30 minute mark, how you can be your own tax lawyer. This is the moment we promised to let you know about after our 2020 analysis: Will lawyers be replaced by GPT-3? Now, with this shadow looming large, I went to cross off one item on my bucket list: Legalweek by ALM. I had no plan, and no purpose except to explore and to experience. Here’s what happened.

We announced our World Tour locations and kept our dates stealthy. It’s a Surinamese superstition to be stealthy about travel. Just as we applaud every safe airplane landing we are in. However, I did mention Legalweek to a few friends, and they graciously invited me to meet. And that’s the first tip for all Legalweek rookies: meetings. No matter if you are a visitor or a vendor: the goal is to get meetings with people in person. We had 2 meetings planned before our arrival. On departure, we had completed 24 meetings in a three-day time span. We missed the parties since we were wiped out by 5 PM and awake at 1 AM every night.

Heroes

Doing meetings almost made us miss the coolest part of Legalweek: exhibitors. There were three exhibition halls and we discovered the 3rd only later. These halls were filled with heroes, and I admired all who paid to make the trip to New York. Not only the sponsors and exhibitors, but also the visitors. Our rough estimate was 4000+ in attendance, all with one passion: working with legal. That’s why Legalweek was on my bucket list. Was it larger before the pandemic? Maybe. Will the next one be even bigger? For the prosperity of all, we sincerely hope so.

How could Legalweek grow? We need more heroes. Visibility is a valuable investment, and that’s why conferences are irreplaceable. However, deciding to show up would have been tough for most. Based on our calculation, most can not afford a big splash funded purely by revenue. The legal tech unit economics are like every other: products x price minus operations. We have fair benchmarks on both operations and prices per area. These benchmarks are generated using a large curated dataset. Given the pullback in spending by companies across the globe, the decision to attend took courage. Yes, even for those with access to outside capital.

Overwhelming

Wandering Hilton, with these numbers on my mind, made this experience surreal. Because most of whom I met, and every vendor I saw, is a row in our dataset. Each is input to an equation on areas, segments, and geographies. Suddenly, the input had faces and voices and they talked to me. Imagine meeting movie stars at the Oscars. You know their movies, but you expect them to not know you. When I met Jack Newton, CEO of Clio, he said to me: I know who you are, and I like what you do. I had a hunch, since he had liked two tweets. Nevertheless, I was overwhelmed, and I kept that feeling until I landed in Amsterdam.

Why overwhelmed? The diverse faces and voices I met, in most cases for the first time, gave me hope. We knew we have enemies, now we know we have friends too. In all honesty, both originated from our ideas about the legal industry. We believe numbers matter and aren’t swayed by narratives. At Legalweek, we had those conversations with the people we met. It’s not all bad because the good news is usually hiding in data. Starting this Thursday, we’ll share the photos of our Legalweek adventure on LinkedIn. So follow us to see Heroes.

To be continued every Thursday…

As a society, we evolve and make new laws. Laws are based on opinions we’ve formed after processing new information. What is new information?

TLDR: Thursday, 23 February, we presented our vision of the future of law. And our dream is data.

Hallucinations

We’ll focus less on numbers this outing. The numbers aren’t pretty, so let’s not pile on. On the bright side, it seems we’ve hit bottom. We calculated a recovery around February. A calculation we shared back in August 2022 with Law.com. Evidence in support: the US Federal Reserve only raised the interest rate by 0.25 this February. Previously, they raised rates by 0.50 and 0.75. Don’t pop the champagne because we are not an economist. Worse, most economists are actually sober about what lies ahead.

Another bright spot we shared with Law360 in early 2023: an avalanche of A.I. legal apps focused on consumers. All running on OpenAI. Talk about building a house in your neighbor’s backyard. This follows two other insights we shared. First, OpenAI is an operating system powering a new paradigm of tools. Second, by their own admission, OpenAI, and most apps build on top, will struggle to turn a profit. Remember, ChatGPT is a killer app, built by a non-profit receiving substantial backing from those with foresight. Realize, that we lack these ingredients in Europe and most other places except perhaps China.

Yet, working on something as fuzzy as “artificial intelligence” feels delirious. Note that the OpenAI dataset cut-off is 2021. You can ask ChatGPT to check this fact itself. So whenever GPT is faced with something after 2021, it will hallucinate. According to Wikipedia: artificial hallucination “is a confident response by an AI that does not seem to be justified by its training data”. This brings us to the point of this analysis: can we distinguish fact from fiction, and will we care? Welcome to a world of weirdness, which is our reality.

Euphoria

Now humans fake it until they make it all the time. Heck, the entire venture capital ecosystem is predicated on one principle: confidently project growth without proof of product-market fit. We closed 2022 with $496 Billion in capital committed to 696 funds looking to invest. This boils down to the craziest stat we’ve ever calculated: $1.3 Billion a day. That is how much is available for those looking for cash. Who’s getting a check? Here is a calculated answer. Contrast this with the reality that fewer tech companies are being founded. And the ones that already exist will struggle to grow.

Now that we’ve established that neither computers nor capitalists need facts to make decisions, the rest of us do, right? Yes, but we rely on computers that are funded by capitalists. Since we’re banning TikTok everywhere in the West, it’s obvious we don’t trust computers from communists. While spying is often offered as the reason, the underlying fear is seldom articulated: influence. With Brexit and Cambridge Analytica still fresh in our minds, it’s clear what guides our decisions: algorithms. In “A.I. the struggle“, the mini-documentary shows the stats and stories which illustrate the challenge. The dollars behind the data we need for our decisions are too overwhelming to dampen.

Surely, the law and lawyers can stop it, right? Actually, legislators created this problem in the first place. And lawyers are ill-equipped to handle any of it. Currently, before the US Supreme Court, there are a few cases around a law named section 230. This law allows those who create algorithms to not be liable for their impact. Pretty sure the lawyers confidently presented a legal argument, with no legal precedent, to sway the Supreme Court. The exchanges that followed revealed that those arguments weren’t convincing. As Justice Kagan admitted about the Supreme Court: “These are not like the nine greatest experts on the internet.”.

Dreams

It’s likely that the courts will kick these cases back to congress to legislate. Herein lies the paradox, neither legislation nor litigation solves these problems. In “A.I. the struggle”, we pitted the Video Assisted Referee (VAR) against Goal-line Technology. If you watch Football every weekend, you know the drama with VAR. The VAR is nowhere as consistent as Goal-line Technology. Ultimately, that is the dream: rational, data-driven legal decisions. More than a copilot, much like an autopilot. Call it Autolaw. Are we there yet? Promise, we’ll let you know when.

Meanwhile, catch this clip, which we made six years ago to illustrate this legal industry journey. And promise us to think about the path our society is on.

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