Scoutbee's 16-18 month journey building LLM-powered supplier discovery through four production stages
Scoutbee, a supply chain supplier discovery platform serving enterprises like Unilever and Walmart, wanted to bring LLMs into a new generation of their product, but foundational models lacked domain knowledge about supplier discovery, produced hallucinated results, and raised enterprise data privacy concerns.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits supplier query
A user begins a conversation with the supplier discovery system by submitting a problem statement.
After introducing RAG with Chain of Thoughts prompting, hallucinations drastically reduced and testing became much easier. Results now include citations with data provenance, allowing users to trust and verify the source of each supplier answer.
What failed first
The initial ChatGPT API integration failed because foundational models lacked domain knowledge and hallucinated fake suppliers. A subsequent agent-based approach remained unpredictable and nearly impossible to debug, with agents randomly fabricating supplier answers even after domain adaptation and guardrails were introduced.