Addressable wedge
70K+ firms
Indian law firms, with 5 to 50 lawyer practices forming the cleanest initial buyer segment.
Buyer and investor narrative
The Precedent Hub
For buyers and investors
The law firms already pay for research.The winning product turns private precedent into faster drafting, firmer margins, and a defensible data moat.
The Precedent Hub combines Indian public law, firm-owned work product, and billing-aware telemetry into a system that is compelling to partners buying software and to investors underwriting the category.
ROI thesis
6x payback
Saving one associate 10 hours a month at a Rs 1,500 billing rate more than clears the seat price.
Quality bar
95%+ target
Citation accuracy is treated like a product requirement, not a marketing line.
For firm buyers
Faster matter turnaround, reusable firm memory, and partner-facing proof that the software protects margin instead of adding process.
For investors
Every uploaded matter strengthens retrieval quality, drafting quality, and switching cost at the same time.
Private precedent control room
One matter flow for research, drafting, and buyer-grade ROI proof.
Indian law firstGrounded outputs
Matter research
Find Delhi HC Section 138 outcomes and surface our firm's strongest reply structure.
Live demo logic
Grounded answer
Public law plus private matter memory
Retrieved corpus
12 matters
Delhi HC judgments, NI Act sections, and 4 firm-owned reply precedents.
Drafting posture
Grounded only
Weak support is refused, strong support becomes searchable citations and usable structure.
Bench context
Judge aware
Highlights how similar reliefs were argued, framed, and granted in prior matters.
Matter signal
Citations
9
Firm docs
4
Relevance
0.91
Bench support strengthHigh confidence
Similar relief has a favorable support pattern when combined with the firm's prior reply strategy.
Draft system
Review before filing01
Issue framing grounded in retrieved pleadings and statutes
02
Prayer language adapted to the current facts, not copied verbatim
03
Source pack appended for advocate review before filing
Draft output preview
First draft generated in the firm voice
Opening
Introduces facts, relief sought, and statutory footing with case-linked framing.
Supporting grounds
Pulls the strongest argument order from prior successful matters and refreshes it for current facts.
Source appendix
NI Act 138Delhi HCFirm reply
Buyer proof
Time saved
42 hrs
Search to draft
61%
Partners do not buy "AI" in the abstract. They buy faster turnaround, reusable knowledge, and margin proof.
Investor angle
Every uploaded matter strengthens retention and product quality at once.
The compounding asset is not public law search. It is tenant-scoped precedent plus measured commercial value.
Indian-law-first research and drafting
Firm-scoped knowledge, not public chat alone
Grounded outputs with refusal behavior for weak support
Billing telemetry that converts usage into commercial proof
Platform thesis
A compounding workflow, not a single AI feature.
The product gets better when firms use it. Ingestion sharpens retrieval, retrieval sharpens drafting, and every search or draft adds commercial proof that helps the buyer justify renewal.
Grounded search
Public law plus firm memory in one research surface.
Buyer proof
Time saved becomes margin language and pricing leverage.
Indian-law-first
Built for statutes, judgments, and court-specific workflow in India.
Compounding loop
Private precedent compounds into product leverage.
Search + draft + telemetry
Each lawyer action improves future retrieval quality, future drafts, and the firm's internal switching cost. This is the operating system logic behind the product, not a feature list.
Firms already budget for legal research software.
Private precedent is the missing layer incumbents do not own.
Billing-linked telemetry turns time saved into renewables, not novelty.
01
Ingest firm memory
Pleadings, briefs, memos, and templates become a tenant-scoped corpus.
02
Ground every answer
Research combines public Indian law with the firm’s own successful work product.
03
Draft in context
Outputs inherit structure, tone, and citations from retrieved precedent.
04
Prove commercial value
Usage logs become partner-facing time-saved and pricing proof.
Live product surface
Grounded legal search
Queries across Indian statutes, judgments, and the firm’s own prior work product.
Open demo
Live product surface
Draft generation engine
Notices, submissions, bail applications, replies, and memos built from retrieved support.
Open demo
Live product surface
ROI telemetry
Usage trails become buyer-facing time-saved narratives and renewal leverage.
Open demo
Why now
The gap is not public-law search. The gap is turning a firm's own work product into reusable operating leverage.
Existing tools already trained buyers to pay for legal research, but they stop at public information retrieval. The missing layer is a tenant-scoped system that retrieves private precedent, drafts from that history, and makes the ROI measurable enough for partners to defend internally.
One-line pitch
Your firm's institutional knowledge, turned into a searchable, draft-generating, billing-ready AI assistant.
Case-law databases
Manupatra, SCC Online, Indian Kanoon
Strong public search, but no tenant-scoped precedent engine and no draft adaptation layer.
Generic legal AI
LawPal, AskLAW, Draft Bot Pro
Public corpus only, weak confidentiality story, and no billing-linked commercial proof.
Practice software
THEO, CaseMine
Workflow exists, but the private knowledge moat and draft-generation loop do not.
Commercial map
The budget line exists. The product enlarges what that spend buys.
Pricing ladder
Seat pricing stays inside an understood budget while adding drafting and measurable ROI.
StarterRs 1.5K
ProRs 2.5K
EnterpriseCustom
Initial wedge
Litigation-heavy firms with repetitive drafting pain.
The fastest conversion path is where repetitive notices, replies, and submissions already consume expensive associate time.
Expansion route
Litigation workflows
Corporate and tax knowledge layers
Regional language courts and enterprise controls
Pricing
Priced inside an existing budget line, with a bigger outcome attached.
Buyers already understand per-user research spend. The difference here is drafting, precedent memory, and measured value.
Starter
Rs 1,500 / user / month
Solo and 1-2 lawyer practices
Pro
Rs 2,500 / user / month
3-10 user mid-tier firms
Enterprise
Rs 3,500+ custom
Large firms, hybrid deployment, controls, and APIs
Growth roadmap
Phase 1
Litigation-heavy wedge
Criminal, civil, and arbitration teams with repetitive notices, replies, and submissions.
Phase 2
Corporate and tax layers
SEBI, RBI, CBDT, and advisory-heavy research once the litigation engine is paying back.
Phase 3
Regional court scale
Multi-language research and drafting for Hindi and major regional language jurisdictions.
Trust and diligence
The hard legal-AI objections are part of the product story, not cleanup work.
This page has to clear both buyer diligence and investor diligence. That means accuracy posture, confidentiality posture, and regulatory framing need to be visible without sending people into a PDF.
Hallucination control
Strict grounding, visible citations, and refusal behavior when support is thin.
Confidentiality posture
Tenant-scoped knowledge boundaries and a product story built around firm-owned work product.
Regulatory fit
Positioned as an advocate-reviewed research assistant, not a legal practitioner.
Positioning guardrail
Research assistant, not a practitioner.
Outputs are designed for advocate review before filing. That framing is good product hygiene and good regulatory hygiene.
Data boundaries
Firm-uploaded documents remain part of the firm's private knowledge layer. The moat comes from safe accumulation, not data mixing.
Closing argument
The right way to win legal AI in India is to own the firm's internal precedent layer before the market normalizes around it.
Buyers can already see research, drafting, and ROI proof inside the demo. Investors can already see why each new firm dataset makes the product more useful, more embedded, and more defensible.