Proven with Industry Leaders
Agentic AI moved into production faster than the controls did.
LLM calls and autonomous agents now flow through the same API and identity layer that runs your business — usually with none of the governance that layer was built to enforce.
Agents with no identity
Autonomous agents invoke internal systems with shared keys, not verifiable identities. When something goes wrong, there is no answer to "which agent, acting for whom, on what authority?"
Traffic with no guardrails
Prompts and responses move to and from models with no consistent policy, no PII controls, and no central view of what data is leaving — or whether it should.
Activity with no audit trail
Examiners and risk teams are starting to ask for evidence: who initiated each AI action, what it accessed, and how access was authorized. Most stacks cannot produce it.
You already run WSO2. Now govern AI and agents on it.
We extend the WSO2 platform you operate into a control plane for AI — covering the model layer, the agent layer, and the systems agents are allowed to touch.
Identity for every agent
Treat agents as first-class identities on WSO2 Agent ID and Identity Server — registered, authenticated, scoped to least privilege, and revocable instantly. Every on-behalf-of action traces to an agent, an owner, and an authority.
Governed AI and MCP access
Route, rate-limit, and guardrail LLM and MCP traffic through the WSO2 AI Gateway. Define which agent can invoke which tool or service, under which policy — and block the rest.
Deployed inside your boundary
Run the entire control plane on-premises or in your private cloud, alongside in-perimeter models. Data and decisions stay where residency and sovereignty rules require.
Evidence built for examiners
Produce the audit trails, access records, and policy reports regulated review actually asks for — designed with the compliance control in mind, not bolted on afterward.
Whether your MCP layer lives in-perimeter on the WSO2 AI Gateway or in Bijira's MCP hub (see Bijira vs API Manager), the governance question is identical: which agent, which tool, whose authority, and where's the record. We design the control so the answer doesn't depend on where WSO2 hosts the plumbing. If the gateway layer itself is new to your estate, start with our guide to what an AI gateway does and when you need one.
Stand it up. Govern it. Keep it running.
Whether WSO2 is already core to your stack or arriving with your next project, we cover the full arc — and stay on to run it.
Build it AI-ready
New to WSO2, or rolling it out across North America? We deploy the API, integration, and identity layers ready for AI and agents from day one — so governance is designed in, not retrofitted.
Bring agents under control
Apply identity, guardrails, and audit to the AI and agents already moving through your platform. This is where the regulated stakes are highest — and where our depth shows.
Managed services
We keep the platform current, secure, and governed as it scales — so your team ships product while the control plane stays sound.
Proven depth on the platform — and the regulator.
WSO2 is moving its identity and integration stack to the front of the agentic-AI shift. We deliver that stack where the stakes are highest: regulated, in-perimeter, and audited. Our WSO2 consulting practice stands it up, and our WSO2 support services keep it governed in production.
- → WSO2 delivery partner. We build on the platform itself, not around it.
- → Regulated by default. Deep delivery experience in data-residency-constrained, audited environments.
- → Built on WSO2's agent layer. Agent Manager, Agent ID, and Identity Server 7.2 — applied to real production constraints.
- → One stack, one perimeter. Gateway, identity, and governance delivered as a single control plane inside your boundary.
Agentic integration, governed from the first call
Agentic integration is what happens when AI agents stop answering questions and start acting: calling APIs, invoking tools, and changing records in the systems that run the business. It runs through the same API and identity layer as everything else, so that is where it has to be governed, with an identity for every agent, a policy on every call, and a record of every action.
What is agentic integration?
Agentic integration is connecting AI agents to enterprise systems so they can act, not just answer: calling APIs, invoking tools through MCP, and reading or changing records in core systems. Done safely, every agent has its own identity, every call passes through a governed gateway and policy, and every action leaves an audit record.
How do you give an AI agent its own identity?
We register each agent as a first-class identity on WSO2 Agent ID and Identity Server, authenticate it, scope it to least privilege, and make it revocable instantly. Actions taken on a person’s behalf carry both the agent and the person, so every call traces to an agent, an owner, and an authority.
Can AI agent governance run inside our own perimeter?
Yes. The gateway, identity, and policy layers can run on premises or in your private cloud, alongside in-perimeter models, so prompts, data, and decisions stay where residency and sovereignty rules require.
What audit evidence do risk teams expect for AI agents?
Increasingly, a record of who or what initiated each AI action, which systems and data it touched, which policy allowed it, and on whose authority. We design the logging and policy reporting so that record is produced as the agents run, not reconstructed afterward.
A fixed-scope governance review.
A short, low-commitment engagement: we map how AI and agents move through your WSO2 environment today, where the governance gaps are, and what it takes to close them before they reach an auditor.
New to WSO2, or want it run for you? Same conversation — just tell us where you're starting.