Aidena

— AI STACK RECOMMENDATION

AI Contract Analysis & Risk Detection Platform

End-to-end contract review system combining document parsing, LLM analysis, and risk flagging for legal teams. Scales from startup to enterprise with modular architecture.

Stays alive for 365 days after the last visit.

Legal & HR

AI Contract Analysis & Risk Detection Platform

End-to-end contract review system combining document parsing, LLM analysis, and risk flagging for legal teams. Scales from startup to enterprise with modular architecture.

high confidence

Core Stack ℹ︎

Claude Opus 4

Primary

Best-in-class reasoning for complex legal analysis, contract interpretation, and risk identification with minimal hallucination—critical for legal accuracy.

$0.015/1K tokens

AWS Textract

Primary

Extracts text, tables, and form fields from scanned PDFs and documents at scale. Essential for handling real-world contracts with varied formats.

$1.5/1K pages

Chroma

Primary

Lightweight vector database for storing contract embeddings and enabling semantic search across clause types, risk patterns, and historical contracts.

$0/month

Complete the Stack ℹ︎

Dify

Alternative

Visual workflow builder for orchestrating document parsing, LLM analysis, and risk flagging pipelines without heavy custom code.

$0/month (self-hosted)

Braintrust

Alternative

Evaluation platform for testing contract analysis accuracy, comparing Claude outputs against legal benchmarks, and tracking model performance over time.

$0/month (free tier)

PostgreSQL + pgvector

Alternative

Production-grade relational database with vector search for storing contracts, metadata, risk assessments, and audit trails at scale.

$0/month (self-hosted) or $15+/month (managed)

Getting started

  1. 1Set up AWS Textract to extract text and tables from uploaded PDFs into structured JSON.
  2. 2Use Claude Opus to analyze extracted text for risk clauses, liability limits, payment terms, and legal red flags via prompt engineering.
  3. 3Generate embeddings for each contract and store in Chroma for semantic search across your contract library.
  4. 4Build a Dify workflow that chains document parsing → Claude analysis → risk scoring → database storage.
  5. 5Integrate Braintrust to evaluate Claude's risk detection accuracy against known contract patterns.
  6. 6Deploy with PostgreSQL + pgvector for production scalability, audit trails, and historical contract comparison.
  7. 7Expose via REST API for legal team dashboard integration.
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