THE PROBLEM
Building AI agents is easy. Delivering ROI and accuracy with institutional discipline is the real challenge.
Ad hoc development of agents quickly leads to escalating costs, poor quality, high risk exposure, and compounding production challenges.
Governance gaps
Without organization-wide standards, security, and governance, there is a growing risk of future crises.
Spiraling costs
AI expenses are rising faster than value enterprises are unlocking.
Quality ceiling
DIY built agents hit a quality and accuracy wall without the right infrastructure to self-improve.
Degrading reliability
AI produces code at high velocity, but keeping software reliable, secure and production-ready gets exponentially more difficult.
Two self-improving loops, making agents better on every run
Accuracy rises as specs improve and costs falls as context grows
The infrastructure layer your agents are missing
One platform to run any harness, route any model, and monitor every run, all governed by unified controls.
Built-in harness or bring your own
Run our harnesses, pre-tuned for incidents, releases, and vulnerabilities, or plug in your own agents with full evals and controls.
Claude code
Cursor
Copilot
Codex
Custom
Invoke agents from anywhere
Deploy agents seamlessly from the CLI, MCP, Slack, or Teams and ensure identical behaviour across all environments.
CLI
MCP
Slack
Teams
Webhooks
APIs
Budgets and gates per agent
Set spending limits and confidence thresholds for each agent to stay in control of actions and costs.
Policy engine
Approval workflows
Spend alerts
Connect with the tools your teams already use
Plug in seamlessly to your existing stack, from Slack and Teams to custom APIs, so your workflows stay smooth and your data stays in sync.
