Rehearse the future before you act on it.
Describe a world in one sentence. Noesis compiles it into a calibrated environment, populates it with agents that behave like real people and firms, and lets your agents rehearse every scenario — capture the best case, hedge the worst — before committing a single dollar.
Environments
Calibrated, reusable worlds your agents simulate inside. Each carries a live trust score — how tightly it's grounded to real behavior. Private worlds for your business; shared worlds for the open economy.
Your environments
7 worlds · 4 calibratedRehearse
Don't ask "what's the one number." Ask "what futures are possible, and how do I prepare." Noesis rolls the world forward thousands of times and hands you the best case, the base case, the worst case — and a plan for each.
- Volume lift outruns margin give-back by week 3
- Halo onto adjacent premium SKUs
- Competitor holds price, you take share
- Steady volume lift, thinner margin
- Mild cannibalization of mid-tier lines
- ROI positive but concentrated in 23 stores
- Competitor matches, price war erodes margin
- Cannibalization exceeds incremental demand
- Loss concentrated in high-income stores
Launch in the 23 stores driving 70% of the lift first; stage the rest.
Pre-stock adjacent premium SKUs to catch the halo.
Cap the cut at 6 weeks in the 11 high-income stores most prone to cannibalize.
Hold a 3% margin buffer to absorb a competitor match.
If competitor cuts within 10 days → switch to bundle, don't chase price.
If week-2 volume lift < 8% → roll back, the world says it won't pay back.
Decision boundary
where the decision flips · price × horizonSwarm
Behind every number is a crowd of agents reasoning like real people. Watch them run — step by step, obs → act → reward — and see how closely the simulation tracks reality.
Agent swarm
42K agents · 756/batch × 56 parallelIn focus
8 of 41,980 · liveCalibration
simulated vs realApps
Purpose-built experiences running on top of environments. We build the flagship — an ad-spend planner — so you can see what a calibrated world does for a real decision. Anyone can build the next one.
⭐ Flagship · Ad-Spend Planner
env_ads_dtc_v3 · trust 0.77Apps running on Noesis
build your own →Marketplace
A world is an asset. Sell a calibrated environment, a grounded population, or a validated scenario — or buy one to skip the cold start. The data that grounds a world flows back and compounds. This is the economy that forms on the infrastructure.
Run on Noesis
The real users of a simulation layer aren't people clicking dashboards — they're agents. Before a pricing agent sets a price, or a personal agent accepts an offer, it rehearses the consequence here. One call, and your agent sees the future it's about to create.
# before acting in the real world, rehearse it from noesis import World world = World.load("env_retail_cn_wm80") # trust 0.84 outcome = world.rehearse( decision="cut price 10% on snacks", horizon="8w", rollouts=5000, ) if outcome.worst_case.revenue < 0: agent.hedge(outcome.plan.hedge) # don't walk in blind else: agent.commit(outcome.plan.capture)
// expose Noesis to any agent via MCP { "tool": "noesis.rehearse", "world": "env_ads_dtc_v3", "decision": "reallocate $50k, 4 channels", "return": ["best","base","worst","plan"] } // -> agent gets a calibrated future + a plan // -> logs to your Decision Graph automatically
Connected agents
1,284 live · 190 added this weekDecision Graph
Every rehearsal, every mounted dataset, every real outcome that comes back — it all compounds here into a living map of decisions × populations × results. The more the economy rehearses, the more grounded every future gets. This is what competitors can't copy.