AI-Powered AI Agent Deployment
Turn scattered agent experiments into governed production workflows. We design agent stacks, connect tools, set approval paths, and add telemetry so AI agents can safely do real work.
How It Works
AI that enhances your ai agents
Agent Stack Assessment
Map current coding, support, and operations workflows. Pick the right mix of self-hosted gateways, coding agents, and lightweight local runtimes.
Secure Runtime Setup
Deploy agent runtimes with scoped credentials, workspace isolation, model routing, policy prompts, and human approval checkpoints.
Tooling & MCP Integration
Connect GitHub, Linear, Sentry, PostHog, databases, internal APIs, and document stores through auditable tools and MCP servers.
Governance & Observability
Add logs, traceability, cost controls, secret handling, approval rules, and escalation paths before agents touch production systems.
Integrations
Works with your existing tools
Github, Linear, Sentry, Posthog, Slack, Openai, Anthropic, Google and more. We build the integrations. You keep your workflows.
Frequently Asked Questions
Which AI agents do you support?
We work with common coding and operations agents including OpenClaw, PicoClaw, Hermes, OpenAI Codex, Claude Code, GitHub Copilot, Gemini CLI, Cline, Aider, OpenHands, Goose, Cursor, and Windsurf. We choose based on workflow, risk, hosting needs, and team habits.
Can agents work with our internal systems?
Yes. We expose internal tools through scoped APIs or MCP servers, then add approval gates and audit logs around sensitive actions such as database writes, deployments, customer messages, and finance workflows.
How do you keep agents from taking risky actions?
We use workspace isolation, least-privilege credentials, explicit tool schemas, human approval steps, test gates, secrets redaction, and production-deny policies. Agents can do useful work without getting unrestricted access.
Ready to automate your ai agents?
15-minute call. We'll show you what's automatable.