AgentPM is the agent operations platform for teams running AI agents in production. It captures every agent's actions, costs, deliverables, and outcomes across every LLM vendor and framework, surfaces the patterns no single tool can see, and recommends what to do next. Think of it as the advisor sitting above your agent stack — the one place where you can answer, in real time, what your agents are doing, what it's costing, what's working, and what needs intervention.
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The advisor seat for agent operations.
Your agents run on different models, frameworks, and tools. AgentPM brings every action, deliverable, and dollar into one operational view — and tells you what to change next. The agents are interchangeable. The advisor isn't.
What is AgentPM?
How does AgentPM work?
Connect your agents — Claude, OpenAI, xAI, Gemini, local models, Agentforce, custom runtimes. AgentPM proxies their LLM calls and external API calls, captures structured activity events from each agent, links every action back to a task and a process, and rolls it up into a unified view. The advisor layer watches the data, detects anomalies, attributes outcomes, and surfaces recommendations in a daily brief and weekly digest. You stay in control. AgentPM tells you what's worth knowing.
What AgentPM ships with
Six capabilities that turn agent activity into operational intelligence — led by two no other platform can deliver.
Skills as Portable Capabilities
Write a skill once, run it on any model. AgentPM's <a href="https://funnelists.com/aiki/capability-registry">capability registry</a> decouples the skill from the vendor — the same skill executes on Anthropic, OpenAI, xAI, or local models, and moves with you when pricing or quality shifts. Skills are an asset that compounds across years, not a liability locked to one vendor.
Cross-Vendor Cost Attribution
Every <a href="https://funnelists.com/aiki/llm-cost-attribution">LLM call captured with full cost data</a>, across every vendor — attributable to a task, an agent, a process, or a skill. Vendor consoles only show their own bill; AgentPM is the only place that captures the data needed for a unified, attributable spend view across the whole stack.
Agent Oversight
One operational view of every agent in your stack. Activity timelines, deliverables, failures, and health — across internal agents, external agents, and every vendor they touch.
Advisor Layer
Daily Brief and Weekly Digest from an AI advisor that watches your agent ops. Anomaly detection, vendor performance comparisons, and outcome-attributed recommendations on what to change next.
Process Orchestration
Define closed-loop processes that span agents, vendors, and time. Track end-to-end yield, latency, and cost per process run. See which processes are healthy and which are stuck.
BYO Key
Plug your own Anthropic, OpenAI, xAI, or Gemini API key into AgentPM. Pay providers directly at their rates. Your agent traffic flows through your own accounts under your own data policies.
Who is AgentPM for?
AgentPM is for teams running AI agents in production who need to know what their agents are actually doing. Operations leaders deploying agents across multiple vendors. Salesforce shops running Agentforce alongside other agent frameworks. Founders running multi-agent stacks who can't keep context-switching between five tools to figure out what shipped yesterday. If your agent stack has more than one vendor or more than one framework, AgentPM is the layer that makes it governable.
Why AgentPM instead of an LLM vendor's console?
Anthropic Console, OpenAI AgentKit, and Salesforce Agentforce are excellent for agents on their platform. None of them can tell you what's happening across all your agents on all your vendors — they only see their own slice. AgentPM is the vendor-neutral layer above them. It captures activity, cost, and outcomes from every agent regardless of which model or framework runs it, and synthesizes the cross-vendor patterns no single tool can see. Use the vendor consoles to operate inside their walls. Use AgentPM to operate the whole stack.
Frequently asked questions
<a href="https://funnelists.com/aiki/byok-bring-your-own-key">BYO Key (Bring Your Own Key)</a> means you plug your own LLM API key — from Anthropic, OpenAI, xAI, or Gemini — into AgentPM. You pay the provider directly at their rates. Your agent traffic and prompts flow through your own accounts, under your own data policies.
The advisor seat is the position in your agent stack that sees everything, knows what to look for, and recommends what to change next. AgentPM watches your agents work, captures the data no individual tool can see, and surfaces patterns — like which model produces better results for which task type, where cost is leaking, or which process needs attention. You stay in the decision seat. AgentPM is the advisor sitting next to it.
AgentPM ships with native support for Anthropic, OpenAI, xAI, and Gemini at the LLM layer. At the agent framework layer, it captures activity from Claude Code, OpenClaw, Hermes, CoWork, and any custom agent that emits events through the AgentPM SDK. Salesforce Agentforce and Microsoft Copilot Studio integrations are on the near-term roadmap.
Two ways. Agents emit structured activity events through a small vendored SDK — one event per tool call, LLM call, deliverable, or failure. AgentPM also proxies LLM calls and external API calls through a gateway that captures cost, latency, and outcomes automatically. Together, they give AgentPM full visibility into agent work without forcing every team to rewrite their agents.
AgentPM has projects, milestones, and tasks built in — it works as a standalone operations system. If you already run on Linear, Jira, or Asana, two-way sync is on the roadmap. The point of AgentPM isn't to replace your PM tool. It's to be the layer where agent work, agent costs, and agent outcomes live.
Both are built in. AgentPM joins your meetings, transcribes them, extracts decisions and tasks, and drafts content from what was actually said. The notetaker and content engine are the foundation underneath Oversight — they're the same operational substrate that makes the advisor layer work. You get them in the box.
Observability tools show you traces, prompts, and token counts. They're built for engineers debugging an agent. AgentPM is built for operators running an agent stack — it captures the same telemetry, but rolls it up into operational views, ties it to outcomes, attributes cost to tasks and processes, and recommends what to change. Observability tells you what happened. AgentPM tells you what to do about it.
We're onboarding Early Access users in waves. Sign up and we'll send your spot in line plus a heads-up before your account opens. Funnelists customers and existing AgentPM testers are prioritized.
Join the AgentPM Early Access list
Get an invite when your wave opens. Early users help shape the roadmap.