Building a pilot is easy. Getting to production takes engineers.
95% of enterprise AI projects fail in the lab. We don't just hand you an API key. We embed elite Forward Deployed Engineers (FDEs) to architect, govern, and scale your autonomous AI workforce in your own cloud.
Building a prototype is the easy part. Running a hundred of them is the business we're actually in.
Most AI vendors optimise for the demo: model access, a notebook, and a convincing first result. AgentOS was built for everything that comes after — where every action an agent takes carries an identity, a policy decision and an audit trail, and where a workflow has to survive real approvals, real exceptions and a real budget. That is the part that decides whether a pilot becomes an operation.
Embedded architects
Not a support queue. FDEs act as your hands-on AI CTO. They embed directly with your technical teams, write custom production code, and architect your agent ecosystem from the ground up.
100% data privacy
Deploy AgentOS entirely within your AWS, GCP, or Azure environments. Enforce strict boundaries. Your proprietary models, internal databases, and customer data never leave your virtual private cloud.
Bespoke integrations
We don’t expect your data to be perfectly clean. FDEs build custom data pipelines mapping your disparate legacy systems, mainframes, and complex internal APIs directly into the AgentOS control plane.
Eight things an FDE will build for your enterprise.
VPC deployment
Securely install AgentOS in your air-gapped AWS, GCP, or Azure environment.
RBAC configuration
Define granular roles and zero-trust identities for both human and AI workers.
Legacy API bridges
Connect mainframes and legacy DBs via custom middleware built by our engineers.
Guardrail setup
Enforce deterministic boundaries, set cost caps, and prevent runaway AI loops.
Compliance mapping
Map agent actions and logs directly to strict SOC2 and HIPAA regulatory requirements.
Custom Python nodes
Write proprietary Python tools and logic nodes specific to your niche workflows.
Vector DB tuning
Optimize memory pooling to accurately ground LLMs in your specific enterprise jargon.
Internal handoff
Train your internal technical teams to confidently own, monitor, and scale the platform.
Use their models. Govern them with us. Take your agents with you.
Your choice of model should never decide your governance. AgentOS sits above the model, so routing, quotas, approvals and the audit record stay identical whether a workflow runs on Claude, GPT-4o, or something you host yourself. Change the model and every control, every record and every guarantee comes with you.
Deploying agents requires enterprise answers to enterprise risks.
We handle the heavy lifting of compliance and security.
FDEs enforce strict RBAC boundaries.
“Can we trust this agent not to execute unapproved database writes during a hallucination?”
Nowhere. Deployed in your VPC.
“Where does our proprietary training data and customer context actually go?”
Bring us one workflow.
If your process involves people, systems and AI, our engineers will have governed agents running it in your own cloud — typically inside eight weeks.