Picking Winners in the Continued Convergence of Legal Technologies
There is a pattern of convergence in the legal tech market.
Last week, DraftWise announced the launch of Deal Table to help answer questions like “What’s market standard for this term across all 500 deals in the industry?” Around the same time, DeepJudge launched Negotiation Intelligence in order to give "lawyers the power to respond to 'we never agree to that' by creating an instant analysis of opposing counsel's position". Meanwhile, Centari’s core offering is its Deal Intelligence Platform, specifically targeting "AI-augmented contract negotiation" by leveraging the law firm’s institutional knowledge.
Three overlapping product announcements. Three formerly non-competing players suddenly occupying the same space.
Negotiation intelligence isn't alone. Generative AI tabular review — the ability to extract structured data from thousands of documents simultaneously is another hotly contested product. Hebbia offers its Matrix platform, which processes documents into "an organized, interactive grid where each document becomes a row". Harvey's Vault offers "Review" queries that return answers "in a tabular format" across up to 10,000 files. Legora also offers its Tabular Review feature, which "transforms large folders of contracts into an organized, interactive grid".
Pretty much the same feature. Definitely the same pitch.
Or consider litigation prediction. NexLaw, Theo AI, and Darrow; each offers variations of predictive analytics engines to forecast case outcomes. The promises are nearly interchangeable.
The Consequences of the Great Convergence
This is the Great Convergence of legal tech, and it seems to be accelerating since 2024.
The question isn't whether convergence is happening — the question is what it means for survival in a potential bubble, and how buyers should navigate a marketplace where products, pitches, and promises have become indistinguishable.
When every vendor suddenly offers the same features, buyers face a landscape where competitive differentiation happens at the margins. This means that:
Sales cycles lengthen because buyers must now conduct exhaustive bake-offs between near-identical products.
Evaluation fatigue sets in.
Companies pitching their products face an increasingly convoluted challenge: how do you explain why your offering is meaningfully different when the feature set looks identical?
When differentiation erodes, other factors become decisive: existing relationships, timing, and luck.
This raises two urgent questions for legal tech buyers:
How do you pick the vendor least likely to disappear when the bubble bursts?
How do you protect yourself if a vendor disappears?
Question One: Picking the Survivor
The prevailing wisdom says: follow the money. The company with the biggest war chest is the safest bet because they have the longest runway. Their cash won't run out first. And because VCs have invested heavily, you can assume those VCs did their due diligence — therefore, the company must be solid.
History suggests this is dangerously optimistic. VCs get things wrong regularly.
So, what should buyers actually look at?
Revenue, not funding. Companies that generate sustainable revenue from paying customers have demonstrated product-market fit. Companies that raise large rounds have demonstrated storytelling fit. These are not the same thing.
Customer concentration. How dependent is the vendor on a handful of large clients? Diversified customer bases weather downturns better than those reliant on three flagship accounts.
Technology debt. Is the product a thin wrapper around someone else's LLM, or does it have proprietary infrastructure that would be difficult to replicate? When OpenAI changes its pricing or Google launches a competitive feature, how exposed is this vendor?
Team background. Are the founders former practicing lawyers who lived the problem, or technologists chasing a market opportunity? The former are more likely to stick it out through adversity. That matters.
Burn rate relative to runway. A company with $50 million in the bank burning $5 million monthly has 10 months. A company with $20 million burning $1 million monthly has 20 months. The latter is more resilient.
However, most of this data is private. You can't see burn rates. You can't verify revenue claims.
The answer is you probably can't pick the survivor with high confidence. Which brings us to the second question.
Question Two: Surviving When the Boat Sinks
If we assume that a significant number of legal tech vendors won't survive the next downturn — and the data suggests this is likely — how do you ensure that their failure doesn't cripple your operations?
Own your IP. Insist on contract language that gives you ownership rights to any custom configurations, workflows, or trained models specific to your firm. If the vendor disappears, you should be able to extract and port that work.
Demand data portability. Your contracts, precedents, and matter data should be exportable in standard formats (not proprietary schemas locked to the vendor's platform). Test this regularly. "We will give you an export when you need it" is not the same as "here’s an export you can download".
Maintain parallel capabilities. Don't let critical workflows become 100% dependent on a single vendor. Keep traditional processes documented and operational, even if you're not using them daily. This is analogous to business continuity planning.
Invest in your people. If the AI tools disappear tomorrow, can your team still do the work? Upskilling isn't just about adopting new technology, it's about ensuring your people can function with or without it. GenAI should not replace expertise.
Build in escape hatches. Contract terms should include provisions for what happens if the vendor shuts down, gets acquired, or pivots away from your use case. If you have a lot of bargaining power, you can ask for eEscrow agreements for source code, transition assistance guarantees, and clear SLA penalties for non-performance.
Diversify your vendor stack. Don't consolidate everything with one provider just because they've expanded to cover all your needs. The convergence makes this tempting — one vendor, one contract, one integration point. Redundancy costs money upfront but saves far more when vendors fail.
Should Buyers Think Like VCs?
Should buyers pick vendors the same way that VCs pick investments?
We discussed this question with Conan Hines once upon a time.
We have come to change our view a little bit since 2024. VCs expect two thirds of their investments to fail to return principal. VC strategy often is not trying to pick the winner — it is to construct a portfolio where one or two massive successes compensate for the many failures. They diversify across 20-30 companies, reserve capital for follow-on investments in winners, and accept that most bets won't pay off.
Legal tech buyers should not adopt the same approach!
VCs have liquidity events. When a portfolio company succeeds, they exit and realize returns that offset their losses. Legal tech buyers don't have that luxury. When a vendor fails, the customers don't just lose money. Legal tech buyers lose institutional knowledge, face disruptions to operations, migration costs, and risk regulatory or client service failures.
More fundamentally: VCs diversify because they can't predict winners in advance. But legal tech buyers not trying to predict unicorns — the key success metrics are to have a functional piece of software and avoid operational disasters.
What Predicts Survival?
If we look at companies that survived prior bubbles — the dot-com crash, the 2008 financial crisis — what characteristics did they share?
They solved fundamental problems, not trendy ones. Email survived the dot-com crash because people genuinely needed asynchronous digital communication. Pets.com didn't survive because "online pet food delivery" was a solution looking for a problem.
They built defensible moats beyond technology. Network effects, switching costs, regulatory relationships, etc. — these protect companies when the technological advantage erodes.
They maintained discipline during boom times. Companies that grew sustainably, watched their burn rates, and resisted the temptation to overhire survived. Those that scaled on the assumption of infinite capital didn't.
In legal tech terms: The tool that genuinely reduces costs by 30% has staying power. The one that offers "AI-powered insights" (read: a chatbot wrapper around GPT-whatever) does not.
The Path Forward
The Great Convergence reveals that legal tech has become a market driven more by technological possibility than customer necessity. That's not inherently fatal — many valuable innovations start that way — but it is inherently risky. In the current macroeconomic environment with a potential AI bubble inflating, that risk is at its peak.
Our bet is that the winners — both tech vendors and customers — will be those who return to fundamentals:
solve real problems,
build sustainable businesses,
prepare for failures, and
construct portfolios.
