Stop guessing.
Start optimizing.
Describe the problem in plain English.
Intellign works out the best schedule, route, or assignment for your team, and shows you exactly why, so the result is one you can trust and defend.
Guesswork has a cost.
Most businesses just don't see it.
Scheduling hundreds of nurses. Routing delivery fleets across a city. Assigning field officers to districts. Every growing operation runs into puzzles like these, solved today with expensive software, endless spreadsheets, or a manager's best guess. Standard AI chatbots don't help: they can talk about the problem, but they can't reliably do the math.
Two ways
to work.
Same engine underneath. Pick the surface that matches you, a chat for teams moving existing tasks in, a structured playground for developers who want to wire it by hand.
Move existing optimization tasks into a chat.
Hospital schedulers, logistics ops, public-sector planners, describe the goal, drop in your CSVs, and Intellign builds the problem with you. No syntax, no modelling expertise, but every step shows its work: the data it read, the columns it understood, and how it worked out the plan.
- Active-problem context bar, readiness checks tell you exactly what's missing.
- Optimization runs in a live view: watch progress, expand goals, review assignments without losing your place.
- Every assignment row carries a rationale, auditable by ops, defensible to compliance.
- Dataset preview and progress are inline in the conversation, never behind a modal.
Illustrative interface, explore the real thing in the live demo.
Built against a national-scale deployment.
Intellign's pilot case study assigns NYSC healthcare graduates to primary health facilities across Nigeria, matching specializations, honouring capacity, prioritising disease burden. It's the same scenario you can click through in the live demo.
Four steps from question
to assignment.
The same four steps run whether you're rostering nurses, routing deliveries, or placing teachers. Intellign handles the solve; you handle the goal and the review.
returned in 4.2s.
One engine.
Multiple industries.
The same Intellign engine routes deliveries, schedules nurses, places teachers, allocates field officers. Anywhere a human is matching resources to demand by hand or by Excel, the engine fits.
One call from any LLM.
Intellign ships a Python SDK and an MCP server your assistant can call as a tool. Describe the problem, post the resources, receive an assignment.
When a healthcare model needs to schedule nurses, it calls Intellign. When a logistics model needs to route deliveries, it calls Intellign.
# pip install intellign, call it from any LLM or agent framework. from intellign import Intellign client = Intellign() result = client.solve( goal="Minimize total nurse overtime", constraints=[ "Each ward needs ≥ 3 nurses per shift", "No nurse exceeds 48h/week", ], resources=nurses, targets=wards, ) # → 50/50 assigned, every decision explained result.assignments
Three tiers, plus a
developer revenue layer.
Start free, grow into Pro when you're moving real production work, and let your engineering team call the API directly when an LLM needs an optimisation answer.
- Capped optimization prompts
- Limited dataset size
- 10 datasets per month
- Community support
- Higher usage limits
- Faster processing
- Scheduling, routing, assignment
- Unlimited dataset creation
- Email and priority support
- Unlimited usage
- Custom integrations
- Dedicated support and SLAs
- Advanced compliance and constraints
API access, $0.10/ solve
A revenue layer for teams calling Intellign directly from their own product or AI agent.
- Subscription-based API access
- MCP and function-calling native
- Long-term enterprise contracts
Questions, answered.
Stop guessing.
Start your first optimization today.
Launch the app, describe your problem, and get an explained, ready-to-use plan in minutes.