Enterprise AI

Anaqua - Enterprise AI & RAG Systems for Legal Tech

Built complete AI backend from scratch — RAG systems, autonomous agents, and LLM orchestration for IP management

2+ years
Duration
50% Faster
Key Metric
Overview

About This Project

At RightHub (acquired by Anaqua), we built the entire AI backend from the ground up. This wasn't about adding AI features to an existing product — it was about fundamentally transforming how the platform handled knowledge, search, and decision-making.

The challenge was significant: take a successful IP management platform and infuse it with generative AI capabilities that enterprise customers could trust with their sensitive intellectual property data.

Over 2+ years, we architected and shipped systems now processing thousands of daily queries, enabling legal and IP professionals to work 50% faster while maintaining strict compliance requirements.

Delivery

What We Delivered

What We Built

  • Enterprise RAG systems enabling semantic search across millions of IP documents, patents, and legal filings
  • Autonomous AI agents that analyze documents, extract entities, and make recommendations with human oversight
  • Context-Aware Generation (CAG) pipelines leveraging prompt chaining and session memory for personalized AI
  • Multi-LLM orchestration with intelligent routing between OpenAI, Anthropic, and Gemini

Key Achievements

  • Achieved 50% faster search through vector-based RAG systems
  • Processing 10,000+ daily AI-powered queries with 99.9% uptime
  • Reduced LLM costs by 40% through intelligent caching and routing
  • Pioneered CAG methodology that became a core product differentiator
  • AI capabilities were a key factor in the Anaqua acquisition

Technical Challenges Solved

  • Legal document RAG — custom chunking respecting document structure and citation networks
  • Reliable AI agents — structured output validation and human-in-the-loop for enterprise workflows
  • Multi-LLM cost control — intelligent routing and prompt caching reducing redundant calls by 60%
Tech Stack

Technologies Used

AI & LLM

  • OpenAI GPT-4
  • Anthropic Claude
  • Google Gemini
  • LangChain / LangGraph
  • RAG Pipelines
  • AI Agents
  • Model Context Protocol (MCP)

Backend

  • Python / FastAPI
  • Java / Spring Boot
  • TypeScript

Data & Vector Search

  • PostgreSQL
  • PGVector
  • JSONB
  • LangSmith

Infrastructure

  • GCP / AWS
  • Docker / Kubernetes
  • GitLab CI/CD
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