An action-packed platform for the whole implementation.
From a blank project to a simulated go-live — every step is AI-accelerated and human-approved.
AI writes every artifact. Your team approves.
Requirements, solution designs, config specs, integration maps, test scripts, SOPs, training — all generated from your live system and a knowledge base trained on thousands of supply-chain texts. Nothing ships without a human sign-off.
- Grounded, not guessed — cites real transactions, entities & params
- Generate → Review → Approve loop with full traceability
- Every approval makes the next generation smarter
Text-to-anything. Drive any system in plain English.
The Co-Pilot is Activate's execution engine. Tell it what you want in plain English and it actually does it on the live system — reading each screen, choosing the next action, and verifying the result — across mobile, desktop, and API in one session. Build configs, execute transactions, compare environments, deploy changes.
It's also how Activate tests: point it at a test and it runs the whole flow autonomously, capturing screenshot evidence and an independent pass/fail verdict at every step — no separate test tool. And it's the foundation the Agent Studio is built on: every autonomous agent you publish runs on this same proven engine.
- Mobile · desktop · API in a single autonomous session
- Executes and tests — every action evidenced, every result verified
- The engine that powers Agent Studio — guided or fully autonomous
A/B test reality — before you touch the floor.
Stand up a living simulation of your operation: AI agents acting as your workers, real-world physics, and your live system config. Then A/B test operational, physical, and systemic changes against the baseline — re-slot a zone, change a wave or routing strategy, add a dock door, tweak a config — and measure the impact across hundreds of simulated users. Works for warehouse, store, and other physical operations. No risk to the real floor.
- AI agents power the workers — real-world physics & operations
- A/B test changes vs baseline · find issues in Week -4, not Week 1
- Hundreds of concurrent users — 250 on Standard, 500+ on Advanced
Where the physics gets real.
The flagship Advanced experience: a photoreal Unreal Engine twin of your facility, Pixel-Streamed to the browser, with embodied AI workers who physically walk, drive, scan, and lift under real-world physics — congestion, travel distance, equipment, collisions and all — while your live system follows every move. The highest-fidelity way to A/B test physical layout and equipment changes, and the ultimate stakeholder demo.
- Embodied AI workers under real-world physics, on a live config
- Recreate a real facility from CAD · swap equipment & layout live
- Dedicated GPU instance, streamed to any browser
It optimizes while you sleep.
Pick a metric to maximize — units per hour, cost-to-serve, on-time %, travel distance — and Activate's auto-research engine goes to work overnight. It makes a small change in the virtual world, A/B tests it against your current settings, keeps what wins, and repeats — cycle after cycle, hundreds of times a night — climbing toward the best configuration it can find.
Every experiment is safely reverted to baseline, so nothing touches production. You wake up to a ranked, evidence-backed set of changes for the kind of complex optimization problems no human could brute-force by hand.
- Choose any metric — it optimizes for it autonomously
- Hundreds of A/B cycles per night, each reverted to baseline
- Cutting-edge auto-research for your hardest optimization problems
baseline 96.2▲ +23.3%
Build autonomous agents. No code.
Compose agents from goals, triggers, and capabilities, then publish them to run on a schedule or on live system events. Every run is scored against the real system with token, cost, and latency accounting — evidence-gated, never a premature victory.
- Priority-weighted goals with checkable success criteria
- Evidence-gated verdicts — no "premature victory"
- Bring your own LLM — Fireworks, OpenAI, Anthropic, Google
See bottlenecks. Forecast labor. Optimize slotting.
A functional digital twin builds a spatial model straight from your config — no CAD — then runs analytical pick simulations to surface congestion heatmaps, LPN journeys, and throughput KPIs. An 11-model forecasting engine plans demand and labor with backtested accuracy.
- Congestion & pick-velocity heatmaps from real layout
- Demand & labor forecasting with WMAPE accuracy KPIs
- Cheap to run — pure analytics, no GPU