Intelligent Legal Assistance for Every Indian Citizen
Production-grade · 5-Agent Pipeline · Dual-Side Marketplace · BNS / BNSS / IPC / CPC / CrPC
- What is NyayaAI?
- The Problem
- How It Works
- The 5-Agent Pipeline
- Dual-Side Marketplace
- Lawyer Portal
- System Architecture
- Data Model
- Tech Stack
- Build Phases
- Success Metrics
- Roadmap
NyayaAI is a multi-agent legal platform that gives Indian citizens instant access to verified legal guidance — and connects them to real lawyers through a transparent marketplace.
| Version | v4.0 — Full Dual-Side Marketplace |
| Platform | Web App + Mobile PWA |
| Languages | Hindi · English · Hinglish |
| Legal Corpus | BNS · BNSS · IPC · CrPC · CPC |
| Status | Final — Ready for Development |
- 🧑💼 Lawyer Dashboard — Full professional portal for advocates
- 📋 Available Cases Feed — Lawyers browse open citizen cases
- 🔄 Case Pipeline — Pending → Offered → Active → Completed
- 🎯 Speciality Feed — Cases matched to declared domains
- 🚨 Unassigned Queue — Prevents cases from going stale
- 🔬 Lawyer Legal Explorer — Professional AI research tool
- Legal info is fragmented across hundreds of acts and state-level variations
- India's 2023 criminal law overhaul (IPC → BNS, CrPC → BNSS) left most resources outdated
- Professional consultation costs ₹2,000–₹10,000+ — out of reach for most
- Lawyer discovery is 100% word-of-mouth — opaque and geographically limited
- District court advocates have no digital channel to reach clients
- Cases arrive cold — no context, wasting the first consultation on intake
- No tool to research BNS/BNSS alongside legacy IPC/CrPC
- Junior lawyers outside metros struggle with unpredictable client acquisition
| Gap | NyayaAI Solution |
|---|---|
| Lawyers invisible outside personal networks | Verified marketplace with AI matching |
| Citizens arrive without context | AI brief dispatched before first contact |
| No fee transparency | Fee ranges + in-platform negotiation |
| No BNS/BNSS research tool for lawyers | Legal Explorer with full corpus |
| District lawyers have no lead pipeline | Available Cases feed filtered by speciality |
flowchart TD
A([👤 Citizen Opens NyayaAI]) --> B[Describe Legal Situation]
B --> C{Intake Agent}
C --> D[Guided Q&A + OCR Upload]
D --> E[Fact Summary for Confirmation]
E --> F{Citizen Confirms?}
F -- No --> D
F -- Yes --> G[Research Agent]
G --> H[(Qdrant Vector DB\nBNS / BNSS / IPC)]
G --> I[(Neo4j Graph\nAct → Section)]
H --> J[Strategy Agent]
I --> J
J --> K{Lawyer Needed?}
K -- No --> L[Drafting Agent\nGenerates Documents]
K -- Yes --> M[Marketplace\nTop Matched Lawyers]
L --> N[Explainability Agent\nConfidence Scores + Audit Trail]
M --> O[Citizen Views Lawyer Cards]
O --> P[Sends AI Brief to Lawyer]
P --> Q([👨⚖️ Lawyer Receives Brief])
Q --> R[Reviews Full AI Brief]
R --> S[Makes Offer + Fee Quote]
S --> T{Citizen Accepts?}
T -- Negotiates --> S
T -- Yes --> U[Active Case]
U --> V[Lawyer Tracks Milestones]
V --> W[Case Complete]
W --> X[Citizen Leaves Review]
X --> Y([✅ Profile Updated])
style A fill:#1a1a2e,color:#fff
style Q fill:#16213e,color:#fff
style Y fill:#0f3460,color:#fff
style C fill:#e94560,color:#fff
style G fill:#e94560,color:#fff
style J fill:#e94560,color:#fff
style L fill:#e94560,color:#fff
style N fill:#e94560,color:#fff
Each citizen case passes through five specialised AI agents in sequence.
flowchart LR
subgraph PIPELINE ["🤖 Five-Agent Pipeline"]
direction LR
A1["**Agent 1**\n🗣️ Intake\nGuided Q&A\nOCR Processing\nEvidence Tagging"]
A2["**Agent 2**\n🔍 Research\nBNS/BNSS Retrieval\nState Variations\nSemantic Search"]
A3["**Agent 3**\n🧠 Strategy\nAction Plan\nForum Routing\nLawyer Flag"]
A4["**Agent 4**\n📝 Drafting\nLegal Notice\nFIR Draft\nAffidavit"]
A5["**Agent 5**\n🔎 Explainability\nConfidence Scores\nCitation Sources\nAudit Trail"]
A1 --> A2 --> A3 --> A4 --> A5
end
style A1 fill:#2d1b69,color:#fff
style A2 fill:#1a237e,color:#fff
style A3 fill:#1b5e20,color:#fff
style A4 fill:#e65100,color:#fff
style A5 fill:#b71c1c,color:#fff
| Agent | Role | v4.0 Addition |
|---|---|---|
| Intake | Converts citizen narrative → structured JSON via guided Q&A, OCR, evidence tagging | No change |
| Research | Semantic retrieval from Qdrant + Neo4j — BNS/BNSS primary with state variations | Powers Lawyer Explorer with deeper citations |
| Strategy | Builds prioritised action plan, sets lawyer_recommended flag | Sets fee estimate range for posted cases |
| Drafting | Generates legal documents — Word + PDF export | Generates lawyer case summary card |
| Explainability | Confidence scores, retrieval sources, reasoning chain | Lawyer mode: full HC/SC citation text |
The matching engine scores all available lawyers using 5 weighted factors.
pie title Lawyer Match Score Weights
"Domain Match" : 30
"Jurisdictional Match" : 25
"Outcome Similarity" : 25
"Review Score" : 15
"Availability & Response Rate" : 5
sequenceDiagram
actor C as 👤 Citizen
participant S as NyayaAI System
actor L as 👨⚖️ Lawyer
C->>S: Completes case analysis
S->>S: Matching engine scores lawyers
S->>C: Shows top 3–5 lawyer cards
C->>S: Clicks "Send Case Brief"
S->>L: Dispatches AI-generated brief
L->>S: Opens brief (status → Viewed)
L->>S: Makes offer with fee quote
S->>C: Notifies citizen of offer
C->>L: Negotiates via message thread
C->>S: Accepts offer
S->>L: Case moves to Active pipeline
S->>C: Confirms acceptance
The Lawyer Portal is a separate professional interface — not a citizen dashboard variant. Every screen is built around the advocate's workflow.
flowchart TD
LOGIN([🔐 Lawyer Login\nEmail + Bar Council ID])
LOGIN --> NAV
subgraph NAV ["Lawyer Portal Navigation"]
AC["📋 Available Cases\nAll open citizen cases\nFilter by domain, state, budget"]
MC["📁 My Cases\nFull pipeline management\nPending → Active → Completed"]
MS["🎯 My Speciality\nPre-filtered by declared domains\nNew case badge count"]
UQ["🚨 Unassigned Queue\nCases with no offers\nTime badges + urgency alerts"]
MP["👤 My Profile\nProfile builder\nVerification + completeness"]
LE["🔬 Legal Explorer\nAI research tool\nSection lookup + case law"]
end
NAV --> AC
NAV --> MC
NAV --> MS
NAV --> UQ
NAV --> MP
NAV --> LE
style LOGIN fill:#1a1a2e,color:#fff
style AC fill:#0d47a1,color:#fff
style MC fill:#1b5e20,color:#fff
style MS fill:#4a148c,color:#fff
style UQ fill:#b71c1c,color:#fff
style MP fill:#e65100,color:#fff
style LE fill:#006064,color:#fff
stateDiagram-v2
direction LR
[*] --> Available : Case posted by citizen
Available --> Pending : Lawyer makes offer
Pending --> Available : Lawyer withdraws offer
Pending --> Active : Citizen accepts
Active --> Completed : Lawyer marks complete
Completed --> [*]
note right of Pending
Citizen can negotiate
via message thread
end note
note right of Active
Milestones tracked
Documents shared
Deadline reminders sent
end note
timeline
title Unassigned Case Escalation Timeline
0h : Case posted by citizen
: Appears in Available Cases feed
24h : No offers received
: Moves to Unassigned Queue
: Matched lawyers notified
48h : Still no offers
: "Urgent" indicator applied
: Push sent to top 10 matched lawyers
72h : Still no offers
: Pinned to top of queue — "Critical"
: Citizen offered option to broaden jurisdiction or adjust budget
| Section | Weight |
|---|---|
| Photo & Bio | 15% |
| Specialisations | 15% |
| Fee Structure | 15% |
| Case History (3+ cases) | 20% |
| Verification Badge | 20% |
| Practice Courts | 10% |
| Languages | 5% |
⚠️ Profiles below 60% completeness are ranked lower in citizen search results.
flowchart TB
subgraph FRONTEND ["🖥️ Frontend — Next.js 14 + Tailwind"]
CW["/citizen/* — Citizen Portal"]
LW["/lawyer/* — Lawyer Portal"]
end
subgraph BACKEND ["⚙️ Backend — FastAPI (Python, Async)"]
CA["Citizen API Router"]
LA["Lawyer Portal Service"]
MS["Marketplace Service\nMatching · Brief Dispatch · Offers"]
NS["Notification Service\nRedis pub/sub + Celery"]
TQ["Task Queue\nRedis + Celery"]
end
subgraph AGENTS ["🤖 LangGraph Agent Pipeline"]
AG1["Intake"] --> AG2["Research"] --> AG3["Strategy"] --> AG4["Drafting"] --> AG5["Explainability"]
end
subgraph STORAGE ["🗄️ Data Layer"]
QD[(Qdrant\nVector DB\nLegal Corpus)]
N4[(Neo4j\nGraph DB\nAct → Section)]
PG[(PostgreSQL\nSupabase\nAll Relational Data)]
RD[(Redis\nQueues + Pub/Sub)]
SS[(Supabase Storage\nDocs + Media)]
end
CW --> CA
LW --> LA
CA --> AGENTS
CA --> MS
LA --> MS
AGENTS --> QD
AGENTS --> N4
AGENTS --> PG
MS --> PG
NS --> RD
TQ --> RD
AG4 --> SS
style FRONTEND fill:#1a237e,color:#fff
style BACKEND fill:#1b5e20,color:#fff
style AGENTS fill:#4a148c,color:#fff
style STORAGE fill:#37474f,color:#fff
erDiagram
LAWYER_PROFILES {
uuid lawyer_id PK
varchar name
varchar bar_council_id
boolean verified
text[] specialisations
text[] practice_courts
float win_rate
float review_avg
int review_count
boolean accepting_cases
float profile_completeness
}
CASE_PIPELINE {
uuid pipeline_id PK
uuid case_id FK
uuid lawyer_id FK
enum stage
int offer_amount
text offer_message
timestamp offered_at
timestamp accepted_at
enum outcome
jsonb milestones
}
LAWYER_REVIEWS {
uuid review_id PK
uuid lawyer_id FK
uuid citizen_id FK
uuid pipeline_id FK
smallint rating
text written_review
boolean is_verified
}
LAWYER_SAVED_RESEARCH {
uuid research_id PK
uuid lawyer_id FK
uuid pipeline_id FK
text query
jsonb result_snapshot
}
UNASSIGNED_ESCALATIONS {
uuid escalation_id PK
uuid case_id FK
float hours_open
smallint escalation_level
int notifications_sent
timestamp resolved_at
}
LAWYER_PROFILES ||--o{ CASE_PIPELINE : "engages in"
LAWYER_PROFILES ||--o{ LAWYER_REVIEWS : "receives"
LAWYER_PROFILES ||--o{ LAWYER_SAVED_RESEARCH : "saves"
CASE_PIPELINE ||--o| LAWYER_REVIEWS : "generates"
| Layer | Technology |
|---|---|
| Agent Orchestration | LangGraph (Python) |
| LLM | Claude Sonnet via Anthropic API |
| Vector DB | Qdrant (self-hosted or Cloud) |
| Graph DB | Neo4j Aura Free |
| Relational DB | PostgreSQL via Supabase |
| Embeddings | text-embedding-3-large (OpenAI) |
| OCR | Tesseract + Claude Vision API |
| Backend | FastAPI (Python, async) |
| Task Queue | Redis + Celery |
| Frontend | Next.js 14 + Tailwind CSS |
| Auth | Supabase Auth — OTP / Bar Council ID |
| File Storage | Supabase Storage |
| Document Generation | docx (npm) · ReportLab (PDF) |
| Deployment | Railway (backend) · Vercel (frontend) |
| External APIs | IndianKanoon · eCourts · Gazette RSS |
gantt
title NyayaAI v4 — Hackathon Build Timeline
dateFormat HH
axisFormat Hour %H
section Pre-Hackathon
Lawyer portal UI (9 screens) :done, 00, 2h
Case pipeline schema :done, 00, 2h
Matching engine implementation :done, 00, 2h
Legal Explorer lawyer mode :done, 00, 2h
Escalation + alert engine :done, 00, 2h
section Phase 1 — Core Pipeline (0–12h)
Wire 5 agents to live knowledge :active, 00, 4h
Citizen intake → analysis E2E :04, 4h
Lawyer matching wired to Strategy :08, 4h
section Phase 2 — Marketplace (12–24h)
Brief dispatch pipeline :12, 3h
Case pipeline UI — Kanban stages :15, 3h
Lawyer Profile Builder live :18, 2h
Speciality feed + Unassigned Queue :20, 4h
section Phase 3 — Polish (24–36h)
Full E2E demo flow :24, 4h
Notifications live both sides :28, 4h
Performance optimisation (<45s) :32, 4h
| Metric | Target |
|---|---|
| BNS/BNSS Citation Accuracy | > 98% |
| State Variation Accuracy | > 92% |
| Intake Domain Classification | > 90% |
| Analysis Pipeline Latency | < 45 seconds |
| Metric | Target |
|---|---|
| Cases surfaced to marketplace | > 45% |
| Profile view rate | > 55% |
| Brief dispatch rate | > 30% |
| Offer received within 48h | > 65% |
| Offer acceptance rate | > 50% |
| Metric | Target |
|---|---|
| Brief response rate (within 24h) | > 70% |
| Case completion rate | > 80% |
| Review submission rate | > 40% |
| Unassigned case resolution (72h) | > 75% |
| Median profile completeness | > 80% |
flowchart LR
subgraph NEAR ["🟢 Near-Term"]
R1["Lawyer-side\ndocument drafting"]
R2["eCourts win record\nverification"]
R3["Video consultation\nbooking"]
R4["Payment & escrow\nin-platform"]
end
subgraph MID ["🟡 Mid-Term"]
R5["WhatsApp intake\nbot"]
R6["Regional languages\nTamil · Telugu · Bengali · Marathi"]
R7["Bar Council API\nauto-verification"]
R8["Lok Adalat /\nMediation routing"]
end
subgraph LONG ["🔵 Long-Term"]
R9["Predictive outcome\nsimulation"]
R10["Community feed\nanonymised cases"]
R11["React Native\nmobile app"]
R12["Real-time Gazette\nalerts"]
end
NEAR --> MID --> LONG
style NEAR fill:#1b5e20,color:#fff
style MID fill:#e65100,color:#fff
style LONG fill:#1a237e,color:#fff
| Role | Profile | Primary Needs |
|---|---|---|
| Citizen | No legal knowledge, Hinglish-first | Understand rights · get documents · find affordable lawyer |
| Educated Citizen | English-fluent, urban professional | Fast analysis · self-represent or smart lawyer selection |
| Junior Lawyer | 0–5 years, building practice | Client leads · AI research · profile visibility |
| Senior Lawyer | 5+ years, HC/SC experience | Qualified high-value leads · pre-qualified briefs |
| Law Student / Paralegal | Legal training background | Case research · statute lookup · outcome data |
| Platform Admin | Internal team | Lawyer verification · dispute resolution · quality control |
The following are explicitly out of scope for this version:
- ❌ Court e-filing automation
- ❌ Native mobile app (PWA only)
- ❌ Regional languages beyond Hindi / English / Hinglish
- ❌ Aadhaar-based KYC
- ❌ In-platform payment processing or escrow
- ❌ AI automation of lawyer responses on the lawyer's behalf
NyayaAI v4.0 · Hackathon Build · Full Dual-Side Marketplace · BNS / BNSS / IPC / CPC · 5-Agent Pipeline
Intelligent Legal Assistance for Every Indian Citizen