Deploy AI Agents
Custom AI agents that take real actions in your systems — engineered for production, not for the demo.
An agent that works in a notebook and an agent that works in production are two different systems. The second one has to handle malformed inputs, tool failures, runaway loops, cost ceilings, and adversarial users — and do it while you sleep. We build AI agents for that reality: scoped, instrumented, and hardened before they touch a real workload.
Scope the agent to a job it can actually do
Most agent projects fail because the agent is asked to do too much. We start by drawing a tight boundary around what the agent owns, which tools it can call, and where a human stays in the loop — so the system is reliable by design, not by hope.
Build the architecture, not just the prompt
Production agents need orchestration, state management, tool interfaces, retries, and fallbacks. We design multi-agent and single-agent architectures with explicit failure modes, so the system degrades gracefully instead of breaking silently.
Harden against the real world
Every agent we deploy is penetration-tested against prompt injection, tool misuse, and data exfiltration. We add guardrails, rate limits, and cost controls so an agent can't quietly run up a bill or take an action it shouldn't.
Instrument everything from day one
We ship agents with tracing, evaluation, and monitoring built in — so you can see what the agent did, why it did it, and whether quality is holding up as usage grows.
What deploying an agent with us includes
- ✓Agent architecture and tool-interface design
- ✓Orchestration, state, and memory implementation
- ✓Guardrails, rate limiting, and cost controls
- ✓Prompt-injection and tool-misuse penetration testing
- ✓Tracing, evaluation harness, and monitoring
- ✓Deployment into your infrastructure, with full handover
Frequently Asked Questions
What kinds of AI agents do you deploy?
Customer-facing support agents, internal operations and research agents, data-processing agents, and multi-agent systems that coordinate across tools. If it needs to take actions reliably in production, it's in scope.
Can you deploy agents into our existing infrastructure?
Yes. By default we deploy into your cloud and your accounts, with no dependency on Ingram to keep the system running. You own all the code.
How do you keep an autonomous agent from doing something harmful?
Scoped permissions, human-in-the-loop checkpoints where they matter, hard guardrails and rate limits, cost ceilings, and adversarial penetration testing before launch. Observability then makes anything unexpected visible fast.
How long does it take to deploy an AI agent?
Most agent deployments ship in weeks, not quarters. Engagements typically start with a fixed-scope Deployment Architecture Review that produces a concrete plan and timeline.
Ready to deploy?
Tell us what you're building. We'll tell you what it takes to ship it — reliably, securely, and at scale.