PipeLLM is a production control plane for AI agents. Relay governs model access, Loop runs stateful agent workloads, and Lens records the decisions behind every run.
Enterprise AI control plane
One control plane for production agents.
Relay connects every model, Loop runs every agent, and Lens explains every decision — without changing SDKs.
One endpointPolicy routingManaged tools
Trusted by startups, enterprises, and AI innovators worldwide.
Relay · Loop · Lens
Three products. One control plane.
Relay governs model access, Loop runs stateful agents, and Lens turns every decision into an inspectable record.
01 / Loop · Agent Runtime
Run the agent.
Session state, execution, and agent context stay here.
Sessionsess_checkout_42Tool leasewebsearch attachedStatedurable
Open Loop POST
https://api.pipellm.ai/openai
RelayNode.js
const response = await fetch(
"https://api.pipellm.ai/openai",
{ method: "POST", body: request }
);OpenAIAnthropicGemini
03 / Lens · Observability & Audit
Record the decision.
Route, approvals, and tool activity become traceable evidence.
Tracetr_01H9K6Runs4 completedApprovalpolicy passed
Open Lens Managed tools
Governed by Relay, attached inside Loop, and recorded by Lens.
Current result
✓ approved model selected
Translates protocols and routes requests to approved models.Keep the familiar OpenAI client while Relay reaches the approved model behind it.
1
|
Relay decision
ProtocolOpenAI SDKPolicyapprovedRouteprovider selected

Loop SDK · Agent Runtime
Run the agent. Keep the context.
One Loop call keeps execution, session state, and managed tools attached for the whole run.
import { loop } from "@pipellm/loop";
const run = await loop.run({
agent: "support-triage",
session: "sess_checkout_42",
tools: ["websearch"]
});policy applied before executiontrace opens with the run
Sessionsess_checkout_42state retained
Tool leasewebsearch.attachpolicy allowed
Operator viewapproval trailtrace ready
Lens · Observability & Audit
Decisions you can replay.
See what happened, why it was allowed, and what evidence stays with the outcome.
Decision replay00:03.612
Selected decision03 / 04
A policy gate asks for review.
The requested refund exceeded the autonomous limit, so the action paused for an operator.
- Trigger
- action: refund.create ($286.00)
- Policy
- refunds over $200 require approval
- Outcome
- approved by ops
Evidence bundle
Everything needed to explain this decision stays connected to the trace.
- approver: m.hsu
- policy: refund.threshold
- decision: approved
Pricing that follows the layer you use.
Relay follows provider pricing. Loop and Lens combine a platform base with usage. Build Agent is a scoped professional service.
View all pricingGive agents live context.
Call WebSearch from Loop or your app. Relay governs access, and Lens keeps every tool invocation connected to the run.
Explore WebSearchconst response = await fetch(
"https://api.pipellm.ai/v1/websearch/search",
{ method: "POST",
headers: { Authorization: "Bearer " + process.env.PIPELLM_API_KEY },
body: JSON.stringify({ query: "agent updates" })
}
);
const { results } = await response.json();Insights & Resources
Guides, implementation notes, and production patterns for teams building with AI.
Explore Our Blog
Agent Memory Is the Next Bottleneck in AI Applications
Bigger context windows aren't the answer. The future of AI agents lies in smarter memory systems — semantic retrieval, relational linking, and temporal awareness. Here's why agent memory architecture matters more than raw context size.

Context Engineering for AI Agents: How to Stop Your AI from Forgetting
AI agents lose track of goals during long tasks due to context rot. Learn how LangChain's Deep Agents SDK uses a three-layer compression strategy to manage context windows, and what this means for your AI stack.

Why You Should Use a Unified LLM Gateway Instead of Multiple API Keys
Managing multiple AI provider API keys is a growing pain for engineering teams. A unified LLM gateway eliminates key sprawl, simplifies SDK integration, and gives you the freedom to switch between models without changing a single line of code.
New to PipeLLM? Build faster with the right developer tools. Browse Docs
Start with quickstarts, SDK examples, and production workflow guides.Frequently Asked Questions
Short answers for teams bringing agents into production.
Connect every model with Relay, run every agent in Loop, and explain every decision through Lens.


