Build with Intellign.

Everything here is shipping today. Deeper reference material is being written alongside the API — if something you need is missing, email us and we'll point you at the right endpoint.

1. Launch the app and describe your problem in plain English:
   "Assign 50 nurses to hospital wards. Match specialties
    to ward needs and balance the workload."

2. Pick a data source — upload your CSV/Excel, or let
   Intellign generate a realistic sample dataset.

3. Confirm the compiled goals and say "run it".

That's the whole flow — three turns from question to an
explained, auditable assignment.

POST /ingest/chat/{session_id}        # converse, upload, generate
POST /ingest/files/{session_id}       # upload datasets (csv, xlsx,
                                      # json, parquet, gpkg, ...)
POST /optimizations/run/{session_id}  # dispatch the solve
GET  /optimizations/progress/{job_id} # SSE progress stream
GET  /results/{job_id}                # assignments + metrics
GET  /results/{job_id}/export         # csv / json export

Intellign is built to be called BY other AIs. Expose the
solve endpoint as a tool in your agent framework — when your
LLM needs an optimization answer (rostering, routing,
allocation), it calls Intellign and gets back structured
assignments with per-decision rationale.

MCP server packaging is in active development. Email us for
early access to the tool manifest.