Case study · Legaltech
Legex
An AI legal search engine over Indian case law and statutes. Co-founded and bootstrapped from zero, it cut legal research time by 2.5 days per case, scaled to $120K+ in revenue, and reached the Y Combinator W19 final interview round before being acquired in March 2022.
- Role
- Co-founder, Tech & Product
- Timeline
- 2019 – 2022
- Outcome
- Acquired by Sublime Consulting, Mar 2022
01 · The problem
Legal research was the bottleneck.
Indian law sits across decades of judgments and statutes spread over fragmented sources. For a small firm or an in-house team, finding the right precedent meant days of manual reading before any real work on the case could begin. Keyword search returned noise, and the people doing the reading were the most expensive people in the room.
We saw a wedge: if we could make the highest-frequency, highest-pain task dramatically faster, we could earn a daily habit and a reason to pay.
02 · What we built
Search first, then the workflow around it.
Semantic search over case law
Ranking and retrieval across Indian judgments and statutes, so a lawyer could describe a situation in plain language and surface the precedents that actually mattered, not just keyword matches.
Documentation & compliance automation
Internal tooling that generated and checked legal documentation, cutting service turnaround by 30% and turning a manual, error-prone step into a repeatable workflow.
A product wedge into a slow market
Legal research was the high-frequency, high-pain task. We led with it to earn trust, then expanded into adjacent workflows once teams relied on the search every day.
03 · My role
Co-founder across tech and product.
I co-led product and engineering: shaping what to build, scoping the search and documentation tooling, and making the build-vs-buy calls on each piece of the stack. I ran the early customer conversations that told us research speed was the metric that moved a purchase decision, and we organised the roadmap around defending that number.
We grew the combined Legex and Inbooks team to 8 engineers and 13 interns, and kept the business bootstrapped the whole way, which forced a tight link between every feature and the revenue case behind it.
04 · Outcome
From a research tool to an acquisition.
Legex reached $120K+ in revenue at 3% MoM MRR growth, cut research time by 2.5 days per case, and the documentation automation reduced service turnaround by 30%. The traction and the wedge were strong enough to reach the YC W19 final interview round, in the top 5% of more than 10,000 applicants. Legex was acquired by Sublime Consulting in March 2022.
The throughline I carried forward: lead with the one task that earns a daily habit, tie every feature to a commercial reason, and stay close enough to the build to ship the thing that actually moves the number.
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I'm building in fintech, insurance, and legaltech. Happy to walk through Legex, Inbooks, or my current partnership work at PB Health.