Case Studies

Real projects delivered by our vetted AI engineers across SaaS, e-commerce, and enterprise.

Problem

A B2B SaaS company needed to automate extraction and classification of documents from multiple sources, reducing manual data entry by 80% while maintaining accuracy.

Approach

  1. Designed RAG-based pipeline for document ingestion and chunking
  2. Built classification layer using GPT-4 with structured output
  3. Implemented extraction workflows with LangChain agents
  4. Deployed async processing with retry and validation logic

Outcome

92% extraction accuracy80% reduction in manual work2.5s avg processing time

Production pipeline handling 50k+ documents/month.

Problem

An e-commerce brand wanted real-time personalized product recommendations based on browsing behavior and purchase history.

Approach

  1. Embedded product catalog and user behavior with OpenAI embeddings
  2. Set up Pinecone vector index for similarity search
  3. Built real-time recommendation API with caching layer
  4. Integrated A/B testing framework for model comparison

Outcome

23% increase in conversion18% higher AOVSub-100ms latency p95

Live recommendations serving 2M+ requests/day.

Problem

A legal services firm needed to analyze contracts for risk clauses, compliance gaps, and key terms across multiple document types.

Approach

  1. Architected multi-stage analysis pipeline with Azure OpenAI
  2. Built clause extraction and classification with LangChain
  3. Implemented compliance rule engine and risk scoring
  4. Created audit trail and human-in-the-loop review UI

Outcome

70% faster contract review95% clause detection recallSOC2 compliant deployment

Enterprise system processing 10k+ contracts annually.

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