Engineering partner: Norrvek, Swedenالعربية

Agent Lab · Simulation

Watch an AI agent team work. Then approve the result.

Four scenarios from Gulf operations. Pick one, run it, and see how agents hand off, call tools and stop for a human decision.

Ready
Task

Turn this supplier sheet into a bilingual product listing for our online store.

Input · Supplier sheet · Al Waha Home Supplies
  • Supplier: Al Waha Home Supplies W.L.L.
  • Product: Stainless-steel vacuum flask, 750 ml · SKU AWH-VF750
  • Material: 18/8 stainless steel, double-wall vacuum
  • Performance: hot 12 h / cold 24 h
  • Colours: Silver, Matte Black, Sand
  • Weight: 0.42 kg · Carton qty: 24
  • Available: 10 cartons
  • Cost price: QAR 38.00 per unit
Product listing

Results assemble here as the agents work.

agent-run.log00:00
  1. Intake agentParsed supplier sheet: 1 product, 3 colour variants, 12 fields
  2. Intake agentNormalised units: 750 ml, 0.42 kg, carton of 24, stock of 10 cartons
  3. Catalogue agentMatched the store category Kitchen › Drinkware › Flasks
  4. Catalogue agentMapped 6 attributes to the store schema; colours set as variants
  5. Language agentWrote the Arabic title for Gulf shoppers, not a literal translation
  6. Language agentWrote the English title to the store’s style guide
  7. Language agentDrafted the Arabic description from verified specs only
  8. Language agentDrafted the English description to match the Arabic in meaning
  9. Review agentChecked claims against the sheet: 5 confirmed, ‘leak-proof’ unsupported and removed
  10. Review agentApplied the ‘drinkware-standard’ margin rule to the QAR 38.00 cost
  11. Review agentGenerated the SEO slug; no duplicate found in the store
  12. Review agentQuality checks: 8 run, 7 passed, 1 warning resolved. Ready for approval
Audit trail

The audit trail is written when the run completes.

    Simulation · scripted, no live AI calls

    What you are seeing

    The anatomy of a supervised agent team.

    Specialist roles

    Each agent has one job, its own tools and clear boundaries. Work moves between them like a well-run team.

    Tool calls

    Agents act through APIs and MCP tools with scoped permissions, never through open-ended access.

    Human approval

    Anything that matters stops at a gate. Your people approve, or send it back with changes.

    Audit trail

    Every step, tool call and decision is recorded, so you can always answer “who did what, and why”.

    In a real deployment

    Real agents run on your data, inside your systems, with the AI provider you choose and hosting that meets your data policy. Each one is evaluated for quality, cost and failure modes before it goes live.

    Let’s talk

    Start with one workflow.

    Tell us about a process that slows your team down. In a 45-minute discovery session we show what an agent team could do with it, and what it would take.