The newest way to buy enterprise AI agents from OpenAI does not involve buying anything online. OpenAI Presence, announced on July 22, is a managed product delivered through a limited general availability programme, and the company states plainly that it is not yet available as a self-serve product. Deployments are led by OpenAI’s own Forward Deployed Engineers and a set of selected global systems integrators.
That is a departure for a business that has largely run on API keys and seat licences. Presence is sold as a project rather than a product. Each engagement starts with a single job, such as resolving a billing dispute, handling an insurance claim, or clearing an employee IT service request.Â
The agent is given only the knowledge and system access that the job requires, and the customer writes the rules governing what it can do, when it needs sign-off, and when a person takes over. After launch, Codex reads production sessions and escalations, then proposes changes the customer’s team tests and approves before rollout.
OpenAI’s documentation is unusually candid about the labour involved. Its help centre sets out a six-stage process running from scoping business outcomes, through security, privacy and legal review, simulation and acceptance testing, staged rollout, and post-launch iteration. A Presence agent, it says, does not become production-ready simply by ingesting documents.
The problem this is built to solve is real
The managed model is easy to read cynically, and harder to dismiss on the evidence. Gartner has warned that more than 40% of agentic AI projects will be cancelled by the end of 2027, attributing the failures to governance, undefined business value and weak operational discipline rather than to model capability.
Almost everything Presence bundles is aimed squarely at that diagnosis. Simulations and graders test whether an agent reached the right outcome, followed policy, used its tools correctly and escalated when it should, before anyone outside the company speaks to it. Guardrails intervene when an interaction moves past defined boundaries. Session records and action histories give reviewers something to audit. Escalation paths hand a person structured context rather than a cold transcript, and new versions go out through controlled rollout with rollback.
Enterprises have spent two years discovering that the hard part of a production agent sits in integration, permissions and change management. A vendor that sends engineers to do that work is responding to what buyers have actually been failing at, rather than shipping another dashboard and calling the gap a customer problem.
Where the constraint sits
The trade-off shows up in the eligibility criteria. Access, OpenAI says, depends on workflow fit, implementation readiness and available delivery capacity.
Delivery capacity is a consulting constraint. Software scales; engineers cleared into a bank’s core systems do not. Forward Deployed Engineer is a title borrowed…
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