SECTOR FOCUS · LEGALTECH & PRIVATE ENTERPRISE AIBespoke Engineering & Architecture

Private Enterprise RAG & Verifiable Document Audit Automation.

We design private hybrid search pipelines, layout-aware contract OCR, and review workflows that link findings to source-document citations. Retention and model-provider controls are agreed for each deployment.

Cited

Review FindingsReview speed and citation accuracy require a representative document benchmark.

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PRODUCTION SOFTWARE ARCHITECTURE

Software applications we build for LegalTech & Compliance

Deliverables, acceptance tests, and applicable intellectual property rights are defined in each project agreement. Third-party components remain subject to their own licenses.

pgvector · BM25 · Reciprocal Rank Fusion

Private Hybrid Vector & Lexical RAG Pipeline

Surgical document retrieval combining pgvector dense embeddings with BM25 lexical keyword matching for legal precision.

Core Capabilities

Sub-8-second retrieval across 50,000+ indexed legal agreements

Source-linked clause references with human review and measured citation accuracy

Layout-aware semantic chunking preserving tables, footnotes, and sub-clauses

Deliverables Handover

Vector indexing and chunking ingestion pipeline
Hybrid search API with Reciprocal Rank Fusion (RRF) algorithms
Automated vector similarity benchmark test suite

Delivery Timeline:5–8 weeks

Next.js · Split-Pane Viewer · Annotations

Automated Contract Risk Scorecard Console

Interactive attorney dashboard displaying extracted indemnity risks, breach terms, and non-standard warranty clauses.

Core Capabilities

Side-by-side interactive split-pane viewing original PDF and AI findings

One-click jump directly to flagged source clauses with highlight overlays

Customizable risk policy profiles (e.g. M&A due diligence, vendor MSAs)

Deliverables Handover

Full-stack Next.js legal review console
PDF annotation and bounding-box rendering engine
Executive risk scorecard export in PDF, Word, and JSON

Delivery Timeline:6–9 weeks

Zero-Trust RLS · KMS Encryption · ZDR

Air-Gapped Multi-Tenant Document Governance Vault

Private document storage with client-isolated access controls and configurable retention periods.

Core Capabilities

Customer-managed encryption keys with automated per-client isolation

Automated retention schedules with cryptographically verified data purging

Comprehensive immutable access logs detailing every attorney and API view

Deliverables Handover

Secure document vault architecture on private cloud or AWS/GCP
Automated encryption key management and rotation modules
Audit trail export generator for compliance officer reviews

Delivery Timeline:4–7 weeks

LEGALTECH DIAGNOSTIC60-Second Self-Test

Zero-Data-Retention Document RAG Diagnostic

Evaluate your legal document workflow for AI hallucination risk, review turnaround bottlenecks, and confidentiality exposure in 60 seconds.

Progress:1 / 4

Question 1 of 3

Average Agreement Review Turnaround Time

How many attorney hours are typically spent manually reviewing a complex 100+ page Master Services Agreement (MSA)?

REGULATORY & ARCHITECTURAL RIGOR

Compliance standards & risk mitigations handled

We engineer systems designed to survive third-party regulatory inspections, banking compliance audits, and strict data protection laws.

Privacy

Contracted Data Retention

Model training, logging, retention, and processing terms are selected and verified with each client and provider.

Integrity

Verifiable Clause Coordinates

Risk findings can link to source pages and coordinates so reviewers can verify the underlying clauses.

Security

Air-Gapped Multi-Tenancy

Database Row-Level Security policies are tested for cross-client access boundaries.

Regulatory

Regulatory Alignment (NDPA / UK GDPR)

Configurable retention and deletion controls designed around the client's legal and contractual requirements.

ENGINEERING TOOLCHAIN

Technologies we deploy for LegalTech & Compliance

Python / FastAPIHigh-Performance Document Ingestion

PostgreSQL / pgvectorDense Vector Embeddings

BM25 / Reciprocal Rank FusionHybrid Keyword Retrieval

Claude 3.5 SonnetGrounded LLM Reasoning

Next.js App RouterAttorney Review Console

DockerContainerized Microservices

CLARITY & COMMERCIAL TERMS

Frequently asked questions

Is client contract data ever used to train public or proprietary AI models?

We agree the model provider, processing location, retention terms, and logging controls with each client before deployment. Where zero-retention terms are required, the selected provider and contract must support them.

How do you eliminate AI hallucinations in legal contract analysis?

We enforce grounded citation retrieval. The LLM is restricted to quoting verbatim text extracted from the document coordinates. If a required clause is not found within the document chunks, the system explicitly reports 'Not Present' rather than guessing.

Can this system parse scanned, low-quality PDF contracts?

Yes. Our ingestion pipeline utilizes layout-aware OCR with semantic bounding-box detection, accurately extracting complex tables, multi-column layouts, and marginal notes from scanned documents.

Can our law firm self-host the entire pipeline on our private cloud?

Yes. We deliver containerized Docker microservices that can be deployed entirely inside your organization's private AWS, Azure, or on-premise infrastructure behind your enterprise firewall.

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Ready to build custom software for LegalTech & Compliance?

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