Built for developers, not demos

AI agents that take real action, safely.

Lozedion is the runtime for AI agents that call your real tools, touch your real systems, and get logged like production code, because that's what they are.

Python & TypeScript SDKs · self-hosted or managed · free developer tier
billing-support · agent runs
issue_refund(order #9034)
requested 2 min ago
Awaiting approval
lookup_order(order #9031)
completed in 1.2s
Done
send_email(customer #7742)
running now
In progress
1,204
RUNS TODAY
3
PENDING APPROVAL
0
FAILED
Why agents fail in production

Most "AI agents" are a chat window with extra steps.

They work in the demo. Then they take an action nobody approved, nobody can trace, and nobody can undo. Here's what usually breaks, and what we built instead.

No approval boundary

The agent can send the email, issue the refund, or delete the record, with no human checkpoint in between.

Fix: configurable human-in-the-loop approval on any tool call you mark as sensitive.

No trace of what happened

Something went wrong three steps ago and there's no log of the reasoning, the tool calls, or the inputs used.

Fix: full execution tracing on every run, down to individual tool calls and token usage.

No blast radius limit

One bad prompt and the agent has the same permissions as your most trusted engineer.

Fix: scoped credentials per agent, per tool, with sandboxed execution by default.
The platform

Everything between a prompt and a production agent.

Define what an agent can touch, wire it into your real systems, and see exactly what it does.

Agent SDK (Python / TS)

Define tools, memory and reasoning loops in code you already know how to review and version.

Tool & function-calling framework

Expose internal APIs, databases or webhooks to an agent through explicit, permissioned tool definitions.

Execution tracing

Every reasoning step, tool call and output logged and replayable, so debugging an agent looks like debugging code.

Human-in-the-loop approvals

Mark any tool as requiring sign-off, in Slack, email or your own review queue, before it executes.

Sandboxed execution

Agents run in isolated environments with scoped credentials, so a bad run can't reach further than you allow.

Native integrations

Pre-built connectors for common CRMs, ticketing systems and internal tooling, plus a generic webhook adapter.

Integration

An agent is just a function with tools and a memory.

Define it in code, deploy it like any other service.

agent.py
from lozedion import Agent, tool @tool(requires_approval=True) def issue_refund(order_id: str, amount: float): """Issue a refund in the billing system.""" ... agent = Agent( name="billing-support", tools=[issue_refund, lookup_order, send_email], on_action="log_and_trace" ) agent.run("Customer #4821 wants a refund for order #9034") # every step traced · refund held for approval
How it works

Four steps from idea to deployed agent.

1

Define tools & permissions

Wrap the internal functions or APIs the agent is allowed to call, and mark which ones need approval.

2

Write the agent logic

Compose reasoning steps, memory and tool access in the SDK, version-controlled like any other service.

3

Deploy with guardrails

Ship to a sandboxed runtime with scoped credentials and approval routing already wired in.

4

Observe & iterate

Watch traced runs in the dashboard, catch failure patterns, and tighten permissions where it matters.

Pricing

Free to build. Pay when agents start acting.

Billed on agent runs, not seats. Self-hosted plans available on Enterprise.

Developer
$0/ month

For building and testing agents before production.

  • 1,000 agent runs / mo
  • Full SDK access
  • Execution tracing
  • Community support
Start free
Team
$0.02/ run

For teams running agents against real production systems.

  • Unlimited agent runs
  • Human-in-the-loop approvals
  • Sandboxed execution
  • Native integrations
  • Priority support
Start trial
Enterprise
Custom

For self-hosted deployments and dedicated compliance needs.

  • Self-hosted runtime
  • Custom SLA
  • SSO & audit logging
  • Dedicated support
Talk to sales
FAQ

Before you ask

Can an agent take destructive actions safely?+

Only if you let it. Any tool can be marked as requiring approval, and agents run with scoped credentials so they can't reach beyond the tools you've explicitly granted.

Which LLMs does Lozedion support?+

Any model reachable through an API, via a thin adapter layer. The agent logic and tooling stay the same if you swap models.

Is there a self-hosted option?+

Yes, available on the Enterprise plan for teams that need the runtime inside their own infrastructure.

What happens if an agent gets stuck in a loop?+

Every agent run has configurable step and time limits, and the sandbox terminates any run that exceeds them.

Stop demoing agents. Start shipping them.

Get an API key and deploy your first agent with guardrails already in place.

Get API access