production-ready through
Independent evaluation and training for the AI agent ecosystem. Real-world complexity through simulation environments where agents face multi-hour tasks.
Talk to FounderLarge-scale RL datasets with tuned difficulty distributions. Cheat-proof reward functions. Teach skills scarce in public data (e.g. dependency hell, distributed system debugging).
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.
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.
Explore our research on AI agents, benchmarking, and evaluation
Escaping the maintenance trap: how standardizing our AI evaluation harness with Harbor Framework improved reproducibility and collaboration.
Comparing Google Antigravity and Claude Code for AI-assisted workflows, and why custom Claude Skills might be the better approach.
A reality check on AI enthusiasm: how a simple chart generated vitriolic reactions outside the tech bubble.
The Quesma database gateway IP has been acquired by Hydrolix to ensure continued support.
Read the announcement.