The AI Operations Center Platform
One console for observability, cost intelligence, quality analysis, and operational control across every agent you run.
🔭 Near-Real-Time Observability
See every agent run as it happens — not after a user complains. Full traces across multi-step and multi-agent chains, down to the individual tool call.
Distributed Agent Tracing
Follow a request across every agent, sub-agent, and tool call in the chain, with full context at each hop.
Tool & Function Call Logs
Every function call, retrieval, and API request an agent makes, logged with inputs, outputs, and timing.
Latency & Error Monitoring
Spot slow steps, timeouts, and failed calls before they compound into a broken run.
Run Replay & History
Step back through any past run to see exactly what the agent saw, decided, and did.
💰 Cost Intelligence
Agent spend doesn't look like cloud spend — it's tokens, model calls, and tool invocations that can multiply fast. We bring FinOps-grade visibility and accountability to it.
Token & Spend Tracking
Real-time spend per agent, per model, per prompt version — down to the individual token.
Cost Per Run & Per Task
Know exactly what it costs to complete a task, not just a monthly total buried in an invoice.
Model Cost Comparison
Compare cost and quality across GPT, Claude, Gemini, and open-weight models to route work to the right one.
Budgets, Alerts & Chargeback
Set budgets by team or project, get alerted on anomalies, and allocate cost back to the business.
🎯 Quality Analysis
An agent can be fast and cheap and still be wrong. Continuous evaluation catches that before it reaches your users.
Automated Output Evals
Score agent responses for accuracy, relevance, and task completion on every run, not just in a test suite.
Hallucination Detection
Flag ungrounded claims and fabricated tool results so they get caught before they reach a customer.
Drift & Regression Tracking
Detect quality drops after a prompt edit, model swap, or provider-side update — before it becomes an incident.
Human & LLM-as-Judge Review
Blend automated scoring with human review queues for the cases that need a second opinion.
🛑 Operational Control
Visibility only matters if you can act on it. Set the guardrails once, then let the platform enforce them.
Guardrails & Rate Limits
Cap spend, call volume, and tool access per agent so one runaway process can't take down the budget.
Kill Switches
Pause or stop any agent instantly when behavior looks wrong, without a redeploy.
Approval Workflows
Require human sign-off before high-stakes or high-cost actions execute.
SLOs & Alerting
Set reliability and cost targets per agent and get paged the moment one is at risk.
Works With the Stack You Already Have
OpenAI
Trace and cost-track agents built on GPT-4o, GPT-4.1, and the Assistants/Responses APIs.
Anthropic
Full observability for Claude-based agents, including tool use and multi-agent orchestration.
AWS Bedrock
Monitor cost and performance across every Bedrock foundation model in one place.
Azure OpenAI
Bring enterprise agent workloads on Azure OpenAI into the same cost and quality view.
Google Vertex AI
Track Gemini-based agents alongside every other model provider you run.