Addressable wedge
70K+ firms
Indian firms, with 5 to 50 lawyer practices as the cleanest first buyer segment.
Indian legal AI
The Precedent Hub
Built for firms that already pay for research
Turn your firm's precedent into faster research, sharper drafts, and measurable ROI.
The Precedent Hub combines Indian statutes and judgments with a firm's own work product so lawyers can search, draft, and prove value inside one system.
Existing spend
Rs 1K-3K
Per-user research spend is already normalized by incumbents like SCC Online and Manupatra.
ROI thesis
6x payback
Saving one associate 10 hours a month more than clears the seat price.
Why this wins
Existing tools search public law. The product advantage is turning the firm's private precedent into a reusable operating layer.
Firm-scoped knowledge, not public chat alone
Grounded citations and refusal for weak support
Draft generation built on retrieved precedent
Billing telemetry buyers can actually justify
Why firms switch
The gap is not another legal chatbot.
The real gap is a system that can search the firm’s own work product, generate first drafts from that history, and make the value visible enough for partners to defend the spend.
Public-law databases do not search a firm’s own winning pleadings, memos, and templates.
Generic legal AI can chat, but it cannot become a reusable firm memory layer.
Most tools still promise time savings without converting that usage into buyer-facing ROI proof.
One-line pitch
Your firm's institutional knowledge, turned into a searchable, draft-generating AI assistant.
Product
One product. Three surfaces buyers actually understand.
The landing page should show a real product, not abstract promises. Search, drafts, and analytics each get a concrete surface with a clear outcome attached.
Product tour
Grounded legal research
Natural-language research across statutes, judgments, and private firm work product.
Open demo
Product tour
Draft generation
First drafts of notices, submissions, and replies built from retrieved support instead of copy-paste templates.
Open demo
Product tour
Commercial proof
Usage tracking that turns AI activity into time-saved and margin language for partners.
Open demoHow it works
A traditional three-step product story.
This needs to read like a clear landing page. The story is simple: ingest the firm, use the product in daily work, then prove the return.
01
Ingest the firm
Upload pleadings, notices, briefs, and templates so the product stops acting like a public chatbot.
02
Research and draft
Search stays grounded in Indian law and private precedent, then turns that support into first-draft work product.
03
Prove the value
Every action becomes time-saved telemetry that helps buyers defend adoption and renew spend.
Commercial thesis
6x payback
The pitch is not “AI is interesting.” The pitch is faster work and firmer margins.
Economics
Priced inside an existing budget line, with a bigger outcome attached.
Firms already understand research spend. The additional value is private precedent, better drafting, and usage evidence strong enough to support renewal.
Starter
Rs 1,500 / user / month
Solo and 1-2 lawyer practices
Pro
Rs 2,500 / user / month
3-10 user litigation-heavy firms
Enterprise
Rs 3,500+ custom
Large firms, hybrid deployment, controls, and API access
Why investors care
The budget line already exists because firms already pay for legal research software.
The moat compounds when each uploaded matter improves retrieval quality and switching cost.
Billing-linked usage proof makes the product feel like operational software, not AI experimentation.
Trust
The product still has to clear the hard objections.
Accuracy, confidentiality, and regulatory posture should feel like part of the product design, not an afterthought buried in an investor memo.
Citation discipline
Outputs should stay tied to retrieved sections, judgments, and firm precedent instead of free-form legal advice.
Confidentiality posture
Firm documents remain part of a tenant-scoped private knowledge layer rather than a shared corpus.
Regulatory framing
The product is positioned as an advocate-reviewed research assistant, not a practicing lawyer.
Why not use SCC Online or Manupatra plus ChatGPT?
Because those tools do not turn the firm’s own work product into a private, reusable drafting and research layer.
What makes the product sticky inside a firm?
Each upload improves future retrieval and drafts, so the knowledge base gets more useful and harder to replace over time.
Why does the buyer keep paying?
Because the product attaches to faster turnaround, reusable precedent, and measurable time-saved rather than abstract AI novelty.
Talk to founder
Direct line for investor conversations, early customers, and partnership discussions.
If you want to discuss the market, the product, or an investor demo, reach out directly. The landing page should not hide the human behind the company.