Fleet Ops for AI Agents: One Control Plane for Every Agent You Run

One dashboard shows every agent's status, current task, resource usage, and health — across LangChain, CrewAI, AutoGen, and custom frameworks. Fleet-level metrics give you the big picture: active agents, tasks in flight, aggregate throughput, error rates, and cost burn.

Drill from fleet overview to individual agent traces in two clicks. No context switching between tools. No stitching together dashboards from three different platforms. Everything your fleet is doing, in one place, updated in real time.

Define fleet-wide policies: allowed tools, allowed models, cost limits, operating hours. Fluq enforces them at ingestion time — non-compliant events are flagged or blocked before they cause damage. No more hoping agents follow the rules.

Every policy decision is logged with a full audit trail. Built for teams that need to explain what their agents did and why. When compliance asks “what happened at 3am?” you have the answer in seconds, not hours of log diving.

Fluq catches when Agent A and Agent B both try to update the same resource. Visualize agent interaction patterns: who talks to whom, shared resources, and contention points. Configure resolution strategies — queue, reject, alert, or first-writer-wins — to match your operational requirements.

pip install fluq-sdk
from fluq import Fluq
fluq = Fluq(); fluq.track("agent.status", {"agent": "researcher", "status": "active", "task": "market-analysis"})