Needle and AI Lab Services Partnership
CASE STUDY

Shipping production-ready ESG platforms in days with Needle's API

AI Lab Services needed to create a custom document management and intelligent search platform for ESG compliance. Using Needle's RAG API and AI coding tools, they shipped a white-label solution in days instead of months, complete with multi-tenant architecture and production-grade quality.

AI Lab Services logo
Christophe Fischer

Christophe Fischer

AI Product Builder

SOLUTIONS

Custom RAG Platform for ESG Compliance, White-Label Document Management

PRODUCTS

API IntegrationRAG System
Days
TIME TO SHIP
Production-ready platform delivered in days, not months.
90%
DEVELOPMENT TIME SAVED
Avoided building RAG infrastructure from scratch.
100%
WHITE-LABEL READY
Client can resell to their own customers.

1. Overview

Christophe Fischer is an AI Product Builder with over 10 years of experience in product management. Currently Head of Product at L'Oréal and teaching AI & Product Management at Join Maestro, he specializes in building custom AI-powered products using modern tools like Windsurf, Cursor, and powerful APIs.

When an ESG compliance company approached him to build a custom document management system with intelligent search, he knew traditional development would take months. Instead, he turned to Needle's RAG API and AI coding tools to deliver a production-ready solution in days.

2. Problem

The ESG company had a specific challenge: they needed a custom platform where clients could:

  • Upload and manage ESG compliance documents (PDFs, reports, guidelines)
  • Search intelligently across their document collections using natural language
  • Organize with custom modes for different types of queries
  • White-label the solution to sell to their own customers

The requirements were clear but complex:

Technical Challenges
  • Document processing pipeline: Chunking, embedding, and indexing various file types
  • Retrieval quality: Accurate, context-aware search results from complex ESG documents
  • Multi-tenant architecture: Each client needs isolated collections with separate API keys
  • Custom UI: Branded interface distinct from existing RAG solutions
  • Production quality: Consistent results without manual tuning

As Christophe explained:

"I tried building this with N8N workflows initially, but the quality wasn't there. Too many steps where things failed. I needed every part of the RAG pipeline to be solid: chunking, retrieval, everything."

Building this from scratch would require:

  • Weeks of development time for chunking algorithms
  • Infrastructure for embeddings and vector storage
  • Complex retrieval logic with filtering and metadata
  • Extensive testing for quality and consistency

Time was critical: the client wanted to demo to their customers within weeks.

3. Solution

Christophe built the entire platform using Needle's API and AI coding tools (Windsurf and Cursor), completing it in days instead of months.

A. Rapid Development with AI Coding

Instead of writing code manually, Christophe used AI coding agents:

  • Windsurf and Cursor read Needle's API documentation directly
  • Agents generated implementation code automatically
  • Only minor adjustments needed for custom business logic

"What I did was go into the API documentation, paste the URL to Windsurf, and it read everything. The only annoying thing was documentation needed to be more AI-friendly for scanning, but once I figured that out, it was smooth."

B. Complete Document Management System

The platform includes:

Document Upload & Indexing

  • Drag-and-drop interface for PDFs and documents
  • Automatic upload to Needle collections via add_files_to_collection
  • Tags and metadata for organization
  • Real-time indexing and vectorization

Intelligent Search Interface

  • Custom chat UI with multiple query modes
  • Powered by search_collection API with semantic search
  • Filters based on document types and categories
  • Structured responses with source citations

File Management

  • View, tag, and organize documents
  • list_collection for file browsing
  • delete_file_from_collection for cleanup
  • Integration with Supabase for metadata storage

C. Multi-Tenant Architecture

Each client company gets:

  • Isolated Needle collection with dedicated API key
  • Custom branding in the interface
  • Separate user accounts managed through auth system
  • Independent data with no cross-contamination

"I made them set up a new account with their own Gmail and give me an API key. Now they're running the thing with their own branding, and I don't even need access."

D. Production-Ready Quality

The most important benefit: it worked from day one.

"I used your API to do the chunking, the retrieval, the whole RAG process. The quality was there immediately. I didn't have to tweak anything."

Christophe avoided:

  • Building chunking algorithms
  • Managing embeddings infrastructure
  • Tuning retrieval parameters
  • Handling edge cases and errors

Needle's API provided production-grade RAG out of the box.

4. Conclusion

Christophe's experience demonstrates the power of combining AI coding tools with robust API platforms like Needle:

Key Takeaways
  1. Speed: Shipped in days instead of months
  2. Quality: Production-ready RAG without manual tuning
  3. Scalability: Multi-tenant architecture that clients can resell
  4. Developer Experience: API docs that work with AI coding agents

"If you can provide the chat API with the final answer generation, you can charge for that. It would have saved me even more time building the agentic structuring myself."

What's Next?

Christophe is now exploring Needle for additional use cases:

  • Travel planning agent with hotel review search
  • E-commerce intelligence at L'Oréal with agentic data analysis
  • Training programs at Join Maestro teaching others to build AI products

If you're building custom AI products for clients and need reliable RAG infrastructure, Needle's API provides the foundation you need. Start building today and ship production-ready solutions in record time.

Try Needle today

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