Make AI agents

production-ready through

realistic simulations

Independent evaluation and training for the AI agent ecosystem. Real-world complexity through simulation environments where agents face multi-hour tasks.

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Training Rewards (10-step Moving Average) 0.8 0.7 0.6 0.5 0.4 0.3 0 50 100 150 200 Steps Score

For frontier labs

Large-scale RL datasets with tuned difficulty distributions. Cheat-proof reward functions. Teach skills scarce in public data (e.g. dependency hell, distributed system debugging).

2:42 #operations @YourAIApp Show me response times from affected services. P99 ~3s instead of usual ~50ms. Grafana link

For AI app developers

Measure quality and uncover blind spots. Pick optimal models, tune prompts in a fast-changing world. Benchmark against competitors. Win deals and deliver on performance promises.

Search files My Drive ๐Ÿ“Š Q4 Reports ๐Ÿ“ˆ Strategy docs ๐Ÿ“ˆ ROI Analysis ๐Ÿ“‹ Budget plans ๐Ÿ“„ Analytics ROI_Agentic_AI_Analysis.xlsx Use Case Solution Revenue Savings ROI 24/7 Support Agent Established SaaS $750K $250K 264% Procurment Assistant New Startup $0 $500K 173% Sales Copilot Vendor Upgrade $300K $100K 87% AI SDR Tool Unproven Vendor -$180K $60K -28% Total โ€” $870K $910K 178%

For enterprise buyers

Independent verification of what actually works. Design processes based on real capabilities, not marketing hype. ROI-driven deployment decisions. Move from FOMO to measurable P&L impact.

Latest insights

Explore our research on AI agents, benchmarking, and evaluation

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