Global Search Across Your AI Estate
Search across agents, tasks, connections, workflows, and audit logs from a single entry point — find any resource in your AI estate instantly.
AI agent security, identity, governance, cost, and the engineering behind the control plane.
Search across agents, tasks, connections, workflows, and audit logs from a single entry point — find any resource in your AI estate instantly.
Saved views let AI operations teams restore any dashboard state in one click — cutting investigation setup time and reducing filter errors under pressure.
Set measurable SLOs for task success rate, latency, and agent availability — then alert before users notice. A practical guide for AI agent deployments.
Turn AI activity into board-ready governance reports covering usage, cost, and risk — with scheduled delivery and export for compliance teams.
How an AI operations dashboard correlates agent counts, spend, trust scores, and security events in one view — and what to do when the numbers look wrong.
Go beyond basic dashboards: model comparison, cost-per-team allocation, anomaly detection, and compliance analytics for AI operations teams.
How a per-interaction event model powers AI agent dashboards, cost attribution, and forensic investigation — without additional collection infrastructure.
Tamper-evident audit logs use hash-chaining and signed Merkle proofs to give compliance teams independently verifiable records—no platform access needed.
How to run one readiness programme covering GDPR erasure and EU AI Act risk classification — shared controls, evidence collection, and the 2026-27 timeline.
How app-layer org scoping and database row-level security combine to prevent cross-tenant data leaks in multi-tenant AI platforms—and where each layer fits.
Per-org feature overrides let you enable a capability for one tenant, observe real behavior, and expand gradually — without touching your deployment pipeline.
Plan-based feature flags gate capabilities by subscription tier while per-org overrides enable safe canary rollouts — no deployment pipeline changes required.
How content guardrails enforce policy on every AI agent interaction—blocking, redacting, or escalating PII, secrets, and violations at the trust boundary.
How real-time collaboration on AI workflow canvases works: CRDTs for conflict-free edits, durable working documents, presence, and per-edit authorization.
Register your own LLM provider keys in one encrypted registry, route workloads to the right model, and eliminate key sprawl — without platform lock-in.
Register MCP servers centrally, enforce per-tool permissions and rate limits, and log every invocation for audit — governance that unmanaged connections lack.
Workflow templates let teams deploy proven agent pipeline patterns in one click — spreading best practices and simplifying governance across the organization.
Turn a plain-language description into a reviewable multi-agent workflow draft in seconds. Learn how AI generation works and where human review stays essential.
The three ways to start an AI workflow—cron schedules, signed webhooks, and platform events—and which trigger fits each operational pattern.
How workflow runs execute node-by-node, how per-run spend caps prevent cost overruns, and how to observe, pause, cancel, and retry runs in real time.
A node-and-edge visual canvas lets you compose, version, and audit multi-step AI agent workflows before anything runs — catching gaps that code reviews miss.
Agents running on borrowed human credentials create accountability gaps and excess privilege. Learn why agent-native identity changes the security calculus.
Register, configure, version, and debug every AI agent in your fleet from a single governed control surface with full audit trails and per-agent access control.
Register every API consumer as a named Application with scoped credentials and per-agent access controls — so you can see and revoke what each can do.