Sarge AI

A jurisdiction-aware AI platform that helps law enforcement officers access approved legal authority and draft court-defensible affidavits without hallucinations.

Key Outcomes

• Faster affidavit drafting under real-world time pressure
• First-line AI legal review before supervisor escalation
• 100% citation-backed AI responses from approved sources only

Quick Facts

• Industry: Law Enforcement / Public Safety
• Platform: Secure Web + iOS & Android Mobile Apps
• Architecture: Single-tenant per department
• Services: Product architecture, AI safety design, UX, compliance workflows

Background

Law enforcement officers operate in environments where speed, accuracy, and legal defensibility are non-negotiable. Yet critical legal guidance—case law, statutes, departmental policies—often lives across fragmented systems, PDFs, or institutional memory.

The client set out to build a high-trust AI legal intelligence platform that officers could rely on during patrol, incident reporting, and warrant preparation without introducing new legal or compliance risk.

The mandate was clear:

AI must assist, not speculate. And it must never hallucinate.

The Challenge

Business Challenges

• Affidavits rejected due to missing probable cause or jurisdictional errors
• Rising legal exposure from inconsistent interpretations
• Over-reliance on senior officers for legal validation
• High-pressure environments with little room for second guesses

Technical & Legal Challenges

• AI hallucination risk in a zero-tolerance domain
• Jurisdiction-specific law that varies by department
• Strict CJIS-aligned access control and auditability
• Ensuring AI outputs could withstand legal scrutiny

Operational Pain Points

• Manual affidavit drafting and review
• Slow feedback loops
• Inconsistent application of policy and precedent

The Solution

Stackup designed and built a single-tenant, jurisdiction-aware AI legal intelligence platform, purpose-built for law enforcement.

1. Jurisdiction-Aware AI with Hard RAG Gating

• Strict Retrieval-Augmented Generation (RAG)
• AI responses generated only from approved, published documents
• Automatic refusal when no sufficient legal authority exists
• Every response includes explicit citations:
• Case references
• Statute numbers
• Policy documents

2. AI-Assisted Affidavit System (Core Differentiator)

The affidavit workflow was designed as a compliance safeguard, not an autopilot.

End-to-End Flow

• Officer inputs text, uploads files, or dictates via voice
• AI asks structured follow-up questions
• System validates:
• Probable cause
• Jurisdiction alignment
• Legal consistency
• AI drafts affidavit language without altering officer-provided facts
• Flags:
• Missing probable cause
• Jurisdiction mismatches
• Potentially unlawful actions
• Officer retains full control over submission

Affidavits are standardized per department and fully searchable for precedent reuse and analytics.

3. Secure Mobile Experience for Officers in the Field

• Secure onboarding with OTP, biometrics, and device registration
• Text and voice-based AI chat with citations
• Voice session replay for affidavit dictation
• Integrated perimeter drawing tool for scene documentation
• Designed for use during patrol, not just at a desk

4. Governance, Review & Policy Memory

• Role-based access (Super Admin, Department Admin, Officer)
• Document approval lifecycle: Draft → Submitted → Approved/Rejected → Published
• Daily review of flagged AI responses
• Structured policy memory for approved corrections
• Immutable audit logs for all sensitive actions

5. Enterprise-Grade Architecture & Security

• Single-tenant isolation per department
• Encryption at rest and in transit
• CJIS-aligned access controls
• Immutable audit trails
• Separate Super Admin console for governance and onboarding

Built and deployed over a 6+ month delivery cycle.

Implementation Process

Phase 1 – Architecture & Risk Modeling

• Defined “AI must never do X” constraints
• Designed refusal-first AI patterns
• Modeled jurisdictional isolation

Phase 2 – Core AI & Document Intelligence

• Built ingestion, versioning, and metadata pipelines
• Implemented strict RAG enforcement
• Validated citation traceability

Phase 3 – Affidavit & Mobile Workflows

• Designed officer-first UX under time pressure
• Integrated voice, drafting, review, and flagging
• Implemented department-specific templates

Phase 4 – Governance & Pre-Launch Hardening

• Audit logs, quality metrics, admin workflows
• Pilot preparation for 5 departments

Results (Pre-Launch Signals)

While the platform is pre-launch, early validation showed:

• Increased officer confidence during affidavit preparation
• Reduced dependence on senior officers for first-pass legal review
• Early detection of:
  • Jurisdictional mismatches
  • Missing probable cause
• Clear positioning of AI as a first-line legal reviewer, not a decision-maker