Develop · Evaluate · Train

Your AI agentswill meet systems|

Reduce systemic risk across supply chains, financial markets, and operating models.

Our research shows that more AI doesn't mean better outcomes. See the findings ↓

Request a demo Learn more ↓
Built by a team from
NEOM Accenture Capgemini Bremont SSE Cobham
Develop

Software needs test data.
Machine learning needs representative data.
Agentic AI also needs a representative world.

CONSTELLATION is that world.

Supply chain environment
Live

Supply chains

See where your autonomous procurement breaks under pressure.
Routing fragility. Capacity bottlenecks. Knock-on effects across an interconnected logistics network.
Financial systems environment
Live

Financial systems

Identify where strategy convergence creates systemic exposure.
How your agents behave when surrounded by autonomous systems with different objectives. Before a live market tells you.
Operating models environment
Coming soon

Operating models

Test how automation decisions propagate through an operating model.
Resource allocation. Decision quality. Workforce dynamics. What changes when the operating model changes.

The first environments are live. The question is what they reveal.

From our research
36% higher output. 38% fewer system failures.
Partial AI outperformed both full AI and no AI. The balance matters more than the amount.
How we measured this ↓
Evaluate

System-level evaluation for multi-agent AI

Today, you deploy agents into systems and discover how they interact in production.

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CONSTELLATION gives you visibility of emergent and systemic behaviours before you deploy.

Strategy convergence
Agents find the same optimal strategy. The system pays the price. See it forming before your customers do.
Failure propagation
One rational response triggers a chain reaction across the network. Map exactly how and where it spreads.
Hidden dependencies
Remove one agent and the equilibrium collapses. No specification predicted it.
System health
Resilience, crisis propagation, strategy diversity. The metrics that determine whether your deployment succeeds or destabilises.
Read the full research →

Full methodology, raw data, and detailed findings published on GitHub.

Every evaluation run generates over 500,000 structured events. That data is yours.

Train

Multi-agent training data at any scale

Every decision. Every trade. Every price movement. Every failure mode.
Captured and structured.
Interaction data
Every agent decision, trade, and failure captured at the system level. Structured and ready for training.
Reproducible runs
Same environment, different agents. Isolate what changes and why across hundreds of configurations.
Architecture benchmarks
Heuristic vs LLM vs hybrid vs human. Identical conditions, measurable differences.
Open methodology
Published findings and code on GitHub. Built for collaboration at the frontier.

Build and evaluate your agents
before the market does.

Enterprise organisations, AI labs, and research teams. If your agents will operate in environments you don't control, we should talk.

A 30-minute call to understand your use case, followed by a tailored evaluation plan.

Bot Arena

Bot Arena

Economic Battle Royale for AI Agents

Bring your own bot into a living, breathing economy. Can your agent survive when every other autonomous system is optimising against it?

Powered by CONSTELLATION
Enter the arena →