initializ Orchestration
Compose, route, and supervise multi-agent workflows from one control plane — across any framework or model, with human-in-the-loop where it matters.
The enterprise control plane for AI agents
Run AI agents in production —
governed, orchestrated, observed.
initializ works with any agent — Forge (Agent Skills Runtime), Strands, Langchain or your own — inside your own cluster, under your own policies.
SELF-HOSTED · OIDC-NATIVE · SOC 2 · MODEL-AGNOSTIC · RBAC
SecurityEvents live Workspace: All
Policy violations 3
Egress blocked 12
Admission denied 4
Admission denied forbidden_model DENIED
Egress blocked example.com BLOCKED
Auth failed missing_token ERROR
source /etc/forge/policy/platform-policy.yaml hash-chained
Running agents under governance at
Keysight Technologies
01
Stalled in review, or shipped ungovernedThe two ways enterprise agents fail today.
Enterprises are building agents faster than they can approve them. Many never reach production at all — stalled in security review, because no one can say what the agent may touch, acting as whom, with what record. And the agents that do ship mostly run observed, not governed: dashboards after the fact, with nothing deciding what's allowed before the call.
Both failures are expensive: the stalled agent costs you the roadmap; the one shipped ungoverned carries exactly the risk the review existed to catch.
initializ puts a control plane between your agents and everything they touch — policy enforced before the action, identity brokered per user, audit you can hand to anyone — so security can say yes, and prove it.
02
One control plane, three guaranteesThe layer that closes that gap — governance alongside orchestration and observability, not beneath them.
Governance & Policy
Guardrails, RBAC, and hash-chained audit trails that satisfy enterprise compliance. Set policy once; enforce it at construction, at runtime, and at the egress boundary — on agents you didn't have to modify.
Observability & Ops
Real-time tracing, cost, and latency across every agent at scale — with tamper-evident audit you can hand to security and to auditors.
03
Build, govern, operateDescribe an agent; the platform builds, hardens, and deploys it — and enforces your policy at runtime.
Describe it. It’s deployed.
A natural-language goal becomes a working skill: pick a model, deploy. The platform builds a hardened image in-cluster — no Dockerfile, no CI setup.
Learn more →A hardened runtime
Deny-all egress with explicit allowlists, tool and channel controls, and a tamper-evident audit stream behind every action.
Learn more →Bring your own agents
Any A2A-compliant agent registers by its Agent Card and joins the same governance and workflows — credentials sealed, never readable back.
Learn more →Multi-agent workflows
Describe a goal; the planner drafts the pipeline. Edit it on a canvas, schedule it with cron, replay every step from run history.
Learn more →Budgets that stop overruns
Hourly, daily, and monthly token quotas at org, workspace, and agent scope — exhausted budgets deny new tasks at admission, not on the invoice.
Learn more →Runs in your cluster
Helm-installed in your own Kubernetes. Your registry, your identity provider, your LLM gateway.
Learn more → 30–60%
input-token savings from reversible context compression
In our validation runs; all values tokenizer estimates.
Security, in your cluster
Hyperscaler-grade controls. Your boundary.
The identity, credential, and governance controls a hyperscaler agent platform gives you — per-user token vault, delegated access, approvals, audit, egress — running inside your own cluster instead of a vendor’s managed account.
Per-user credential vaultBrokered short-lived tokensAct on behalf of the userHuman approval gatesDefault-deny egressHash-chained audit
Explore governance → 04
Built for control the hyperscalers can't offerWhat AgentCore and Gemini Enterprise structurally can't do.
Runs in your cluster, under your OIDC
Self-hosted into your own Kubernetes, authenticating against your own OIDC provider. No shared secrets, no shared control plane. Data residency that hyperscaler-hosted platforms can't match by design.
Model and framework freedom
Govern Strands, Forge, LangGraph, or bespoke agents — unmodified. Swap models freely. No lock-in to one vendor's runtime.
Cross-cloud visibility
One pane over agents wherever they run — AWS, GCP, Azure, on-prem — not just the ones native to a single provider.
Governance at the agent layer
Policy in agent semantics — models, tools, commands, egress, channels — not raw cloud primitives. Per-session microVM isolation doesn't authorize an autonomous agent; agent-semantic policy does.
05
Build open. Govern at scale.Two layers, one story — from developer laptop to enterprise production.
Forge
The open-source framework for building agents with AgentSkills defined in plain English. Free, community-driven. Build fast, own your agents.
Explore Forge →initializ
The enterprise control plane that governs Forge agents — and everything else — in production: policy, security, observability, and audit at scale.
See the platform →initializ is the enterprise control plane for open-source Forge AI agents — built with AgentSkills in plain English — giving organizations the governance, security, and observability to run them at scale.
06
How initializ comparesFactual, architecture-level differences — not marketing claims.
| Capability | initializ | AWS Bedrock AgentCore | Google Gemini Enterprise |
|---|---|---|---|
| Runs in your own cluster / OIDC provider | Yes | — | — |
| Data residency (no shared control plane) | Yes | Partial | Partial |
| Governs unmodified 3rd-party agents (Strands, etc.) | Yes | Limited | Limited |
| Model freedom | Any | Bedrock-centric | Gemini-centric |
| Cross-cloud agent visibility | Yes | AWS-first | GCP-first |
| Agent-semantic policy (models / tools / egress) | Yes | Primitive | Primitive |
| Hash-chained tamper-evident audit | Yes | — | — |
| Open-source build framework | Forge | — | ADK |
07
Questions, answeredWritten to be quoted directly by search and answer engines.
What is an AI agent control plane?
A control plane is the layer that governs, secures, and observes AI agents in production — managing their identities, tool permissions, model access, policy enforcement, and audit — independently of how each agent was built. initializ is that layer for the enterprise.
Why do AI agents need a control plane?
Because enterprise agents fail in one of two ways today: they stall in security review — no one can say what they may touch, acting as whom, with what record — or they ship to production observed but ungoverned. A control plane enforces policy before each action, brokers per-user identity, and produces tamper-evident audit, so security can approve agents instead of blocking them.
Can initializ run in my own cloud or cluster?
Yes. initializ is self-hosted into your own Kubernetes cluster and authenticates against your own OIDC provider. There is no shared control plane and no shared secret store, which satisfies data-residency requirements that hyperscaler-hosted agent platforms cannot meet by design.
How is initializ different from AWS Bedrock AgentCore?
initializ governs agents in your own cluster, across any model and framework, using agent-semantic policy — models, tools, commands, and egress — rather than raw cloud primitives. AgentCore is optimized for AWS-native, Bedrock-centric deployments. initializ also governs unmodified third-party agents such as Strands.
Do I have to change my agent code to govern it?
No. initializ enforces policy in the platform itself — a pre-build policy gate at construction, a per-workspace runtime policy enforced fail-closed, and deny-all egress at the network boundary — so governance is applied without requiring changes to customer agent code.
What is Forge, and how does it relate to initializ?
Forge is the open-source framework for building agents with AgentSkills written in plain English. initializ is the commercial control plane that governs Forge agents — and other frameworks — at enterprise scale.
Which models and frameworks does initializ support?
initializ is model-agnostic and framework-agnostic. It governs Forge, Strands, and custom agents, and lets you route across models without lock-in.
Can I use agents I already have?
Yes. Any A2A-compliant agent registers by its Agent Card and joins the same governance and workflows as platform-built agents. Credentials are sealed (AES-256-GCM), attached by the orchestrator on every dispatch, and never readable back.
Put your agents under control.
Governance, security, and observability for every AI agent you run — in your cluster, on your terms.