Enterprise AI Agent Platform | Enterprise Agentic AI Platform - Kodeus
Enterprise

Enterprise AI agent platform

Run it inside your perimeter. Keep the record. Kodeus runs in your VPC against your own database, or fully airgapped with no outbound dependency. Every request carries an identity derived from a verified credential. Every action is attributable, traced and retrievable. The controls are in the runtime, not in a prompt, so they hold when the model changes.

acme-corp·Consolevpc · us-east-1egress · model provider onlylive
Teams
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AgentUsersLast actionState
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Approvals{{ pending }}
payments-agent · user_2210Release payment package $48,200 · above approver caprule spend.cap · held 14:02:04approved · m.chen · recorded in trace
support-agent · user_0977Refund $640 over capapproved · r.patel
agents in production14
isolated users2,310
approvals today{{ apprCount }}
spend this month$412.60
The controls

What the runtime enforces

Each control: what the runtime does, and the evidence you can ask for.

ControlWhat the runtime doesEvidence you get
Tenant isolationOrgs, users, databases and secrets separated at the runtime.Isolation test report
Encrypted credential vaultsAES-256-GCM per user, with rotation and revocation.Key lifecycle events in the trace
Human approval gatesNamed actions wait for a person before they run.Approval record: who, when, what changed
Policy at five checkpoints45 guardrails, fail closed, including one before every tool call.Policy catalogue
Traces and historyOpenTelemetry traces with verdicts, latency and cost.Sample trace
Spend limitsCaps per agent and per user, enforced in the runtime.Cost per agent in the Console
Data residencyConversations, credentials and user data stay in the environment you deploy into. Model traffic goes straight to your provider.Network egress map
Deployment

Four ways to run it. One runtime.

The policy engine, the traces and the isolation model are identical in all four. What changes is who operates it and what leaves the network.

LocalYour cloudKodeus CloudAirgapped
Operated byYouYouKodeusYou
DatabaseYoursYours, in your VPCOurs, per tenantYours
Network egressModel providerModel provider onlyModel providerNone
ModelsAny providerAny provider, your keysAny providerHosted inside the perimeter
Best forDevelopmentProduction under your network policyFastest startSites where the cable is pulled
Evidence for a review

What we can show you

Ask for any of these on the call.

PDF · 14 pages

Isolation test report

Six part adversarial suite, run against release 0.9.4

OTEL · JSON

Sample trace

Rule verdicts, approval record, latency and cost per step

PDF · 45 rules

Policy catalogue

All rules by family, with the checkpoint each one runs at

Live · 30 min

Checkpoint walkthrough

The five checkpoints, with your own tool calls

How an enterprise engagement runs

First agent live, then your team runs without us in the room

We help with the first agent. Then your team owns it. The goal is that the second agent needs no one from Kodeus, because the runtime and the skills carry what was learned from the first one.

1
Week 1

Scope

The use case, the tools it needs, the identity model and the approval boundary.

Kodeus + your team
2
Weeks 2 to 4

Run

First agent live in your environment, with your security reviewer watching.

Kodeus + your team
3
After

Own

Your team ships the second agent. The skills carry what the first one taught.

Your team
Proof

Warren runs on this runtime on live markets with real money. Nash and ARTPARK at IISc Bangalore run on the same core. We did not ship a control layer we had not run under pressure ourselves.

How Warren is built →
The platform

What an enterprise AI agent platform has to hold

An enterprise AI agent platform is the place an agent runs when a security review is part of shipping, not a meeting you schedule after the demo. It is not a library for composing prompts. It is the runtime: isolated per tenant, an identity on every request, credentials encrypted per user, policy that can refuse, and a trace you can hand to a reviewer without reconstructing the day from logs.

Kodeus is that enterprise AI agent platform. You describe the outcome. Kodeus drafts the application, then runs it in your VPC against your own database, on Kodeus Cloud, or fully airgapped with no outbound dependency. The policy engine is the same one you already exercised locally. Moving the agent does not relax the rules. Models can stay inside the perimeter when the network requires it. Spend caps are enforced in the runtime, per agent and per user.

The controls above are the ones a reviewer asks to see: tenant isolation, the credential vault, human approval, policy at five checkpoints, OpenTelemetry traces, spend limits, and data residency. Each row names the evidence, not a slogan. If you want the infrastructure list without the enterprise framing, read AI agent infrastructure. If you want the record of each call, read AI agent observability. Governance, as a practice rather than a deployment boundary, is AI agent governance.

What this enterprise AI agent platform will not do is host an agent you finished in another framework. There is no import of a LangGraph project or a CrewAI crew. The supported path is describe, then build and run, with your team owning the second agent after the first one is live. Warren runs on this runtime under real load. The same core is what you are evaluating for your own perimeter.

FAQ

Questions from security reviews

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Private preview

Bring your security reviewer to the first call.

Thirty minutes. We walk through the runtime, the checkpoint model and deployment in your environment, and you leave with the isolation report.

Book a call