The managed runtime for AI agents

Define, deploy, monitor, and improve AI agents through a single platform. Go from zero to production in 10 minutes.

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terminal

$ agentlift init my-agent

Scaffolding agent in ./my-agent...

Created agent.yaml, prompts/, tools/

$ agentlift deploy

Building agent... done

Deploying to edge runtime... done

✓ Agent deployed successfully

Endpoint: https://api.agentlift.dev/a/my-agent

Dashboard: https://app.agentlift.dev/my-agent

Latency: 42ms p50 · 118ms p99

Shipping an AI agent to production shouldn’t require 7 tools

Today, getting an agent into production means stitching together a model provider, framework, gateway, observability platform, eval suite, deployment pipeline, and vector database. Each with its own account, billing, and docs.

Before — The fragmented stack

Model Provider Framework API Gateway Observability Evals Deployment Vector DB

7 vendors · 7 dashboards · 7 bills

After — One platform

AgentLift

Runtime + Observability + Evals + Deploy + Tools

1 platform · 1 dashboard · 1 bill

Everything you need to ship agents

A single platform that handles deployment, observability, and quality assurance — so you can focus on building.

Deploy in minutes, not days

Run agentlift init, write your config, and agentlift deploy. Your agent is live on the edge with an HTTPS endpoint, API key, and full dashboard — in under 10 minutes.

Observability that's automatic, not opt-in

Because AgentLift owns the runtime, every LLM call, tool invocation, and conversation turn is traced automatically. No SDK to install. No code to instrument.

Quality gates that prevent regressions

Change your model, prompt, or tools — the platform replays real conversations, scores the results, and blocks the deploy if quality drops. Ship with confidence.

How it works

Five steps from idea to production agent.

Scaffold your agent

$ agentlift init my-agent

Generate a project with agent.yaml config, prompt templates, and tool definitions ready to go.

Configure in YAML

Define your model, system prompt, tools, and guardrails in a declarative agent.yaml file.

agent:
  name: my-agent
  model: claude-sonnet-4-5-20250929
  system_prompt: prompts/main.md
  tools:
    - name: search_docs
      type: http
      endpoint: https://api.example.com/search
  guardrails:
    max_turns: 10
    cost_ceiling: $0.50

Test locally

$ agentlift dev

Hot-reload development server with a playground UI. Test conversations, inspect traces, iterate fast.

Deploy to the edge

$ agentlift deploy

One command to push your agent to AgentLift's edge runtime. HTTPS endpoint, API key, and dashboard — instant.

Monitor in the dashboard

Open the dashboard to see traces, costs per conversation, latency breakdowns, and quality scores in real time.

Prefer a browser? Create your agent with our visual builder — no CLI required.

Built for the full agent lifecycle

Everything you need from first prototype to production scale, in one integrated platform.

Runtime

Edge-native execution with sub-millisecond cold starts, streaming responses, automatic failover, and per-conversation cost ceilings.

Observability

Trace explorer with cost per conversation, latency breakdowns, and tool success rates — all captured automatically by the runtime.

Evals

LLM-as-judge scoring, deploy-time regression testing, production sampling, and dataset curation — built into the deploy pipeline.

Developer Experience

CLI-first workflow with hot-reload dev server, declarative YAML config, prompt versioning, and instant rollback.

Web UI

Visual agent builder, conversation playground, drag-and-drop tool configuration, one-click deploy, and team collaboration.

Integrations

Any LLM provider, HTTP and webhook tools, MCP servers, and GitHub PR comments for eval results on every push.

How AgentLift compares

Other platforms give you one piece. AgentLift gives you the whole stack.

	LLM Gateways	Observability Tools	Deploy Platforms	AgentLift
Agent-native runtime	—	—	—	✓
Automatic tracing	—	✓	—	✓
Integrated evals	—	—	—	✓
Deploy pipeline	—	—	✓	✓
State management	—	—	—	✓
Zero-markup LLM pricing	—	N/A	N/A	✓

Other platforms give you one piece. AgentLift is the only platform where routing, deployment, tracing, and evals work together — because we own the runtime.