OpenAI Presence: Enterprise Agent Platform in 2026

OpenAI Presence is a managed enterprise product, announced July 22, 2026, for deploying "trusted" voice and chat AI agents that answer questions, use company systems, take approved actions, and hand off to humans. It is not a developer SDK and not self-serve: deployments are led by OpenAI Forward Deployed Engineers and select systems integrators, and pricing is not public.¹ The headline shift is that OpenAI is now selling the deployed, governed agent — with engineers attached — rather than only the model behind it.

TL;DR

OpenAI launched Presence, a "battle-tested" enterprise platform for putting voice and chat agents into production with policies, guardrails, evaluations, and a Codex-powered improvement loop bundled in.¹ Each agent is scoped to one job and given only the access that job needs. It ships as a limited general-availability, human-delivered engagement — Forward Deployed Engineers do the integration, and there is no self-serve tier or published price.¹² OpenAI says the same system runs its own English-language phone support line, resolving 75% of inbound issues without a human.¹ Presence is not the first enterprise agent platform, but its services-heavy, "rent-don't-build" model is what makes it notable.

What you'll learn

• What OpenAI Presence actually is, and the six things it bundles
• How it differs from building your own agent with an SDK
• The metrics OpenAI put behind it — and how to read them
• Who the early design partners are, and what they are actually doing
• Availability, pricing, and the "engineers attached" delivery model
• Where Presence sits against Agentforce, Copilot Studio, and Vertex AI
• Why this signals OpenAI moving up the enterprise stack

What OpenAI Presence is

Presence is a product for running production AI agents, not a framework for coding them. OpenAI's framing is that proving an agent can work is no longer the hard part — making it "reliable enough to do high-value work in production," and keeping it reliable as products and policies change, is.¹ So Presence pairs model reasoning with "policies, guardrails, and escalation rules that verify accuracy and performance."¹

The unit of deployment is a single job. OpenAI's examples are resolving billing issues, supporting insurance claims, and handling employee IT service requests.¹ For each one, the agent "receives only the knowledge and system access required for that job," and the company sets the policies: what the agent can do, when it needs approval, and when a person should take over.¹ That scoping — narrow job, least-privilege access, explicit escalation — is the governance spine of the product.

The six things Presence bundles

OpenAI describes Presence as bringing together the components teams need to run agents in production. There are six:¹

• Policies and standard operating procedures — the rules and playbooks the agent follows.
• Guardrails — controls that can intervene when an interaction moves outside company boundaries.
• Approved actions — the scoped set of things the agent is allowed to actually do in company systems.
• Simulations — pre-launch tests against common requests, edge cases, and higher-risk scenarios.
• Evaluation tools — graders that check whether the agent reached the right outcome, followed policy, used tools correctly, and escalated when it should have.
• A Codex-powered improvement process — after launch, Codex (using a Presence plugin) investigates production signals and escalations and proposes updates that teams can test against the live version before approving a controlled rollout.¹

The through-line is a full lifecycle: define behavior, simulate it, evaluate it, enforce it, then keep tuning it after real traffic exposes gaps. That last loop — a coding agent proposing tested changes to a customer-facing agent — is the most distinctive engineering idea in the announcement.

Rent the agent, don't build it

The clearest way to place Presence is against OpenAI's own build-it tooling. Teams that want to write their own agents already have the OpenAI Agents SDK, an open-source, code-first framework built around a small set of primitives — agents, handoffs, and guardrails.³ That path gives you maximum control and maximum responsibility: you own the harness, the evals, the deployment, and the post-launch tuning.

Presence is the opposite end of that spectrum. You are not handed a library; you are handed a deployed system that OpenAI's engineers stand up with you. OpenAI says it "works alongside each customer to identify each high-value workflow, connect the necessary knowledge and systems, establish permissions and policies, test the agent, and bring it into production," with OpenAI and systems integrators continuing to support it as the deployment expands.¹ In practice that is closer to a consulting-plus-product engagement than to a SaaS signup — coverage of the launch repeatedly described it as OpenAI shipping "enterprise AI agents with engineers attached."²

For a lot of enterprises, that trade is the point. The hard part of a production agent is rarely the first demo; it is the connective tissue — permissions, policy encoding, escalation design, security review, and the never-ending post-launch tuning. Presence sells that connective tissue as a managed service.

The metrics OpenAI put behind it

OpenAI's strongest proof point is its own support line. Presence powers OpenAI's English-language phone support at 1-888-GPT-0090, and OpenAI says the system "now resolves 75% of inbound issues without human assistance" and that its Codex-powered improvement loop "reduced human handoffs by 15 percentage points in just 10 days."¹ It also says the agent "met or exceeded benchmarks we use to grade frontline human-support quality" within weeks.¹

Read those numbers precisely. They are OpenAI's own, self-reported figures for OpenAI's own support channel — a best-case internal deployment run by the team that built the product. That does not make them meaningless; a 75% autonomous-resolution rate on open-ended phone support is a genuinely hard bar, and a 15-percentage-point handoff reduction in ten days is a concrete claim about the improvement loop working. But they are a vendor's home-field results, not an independent benchmark, and OpenAI has not published comparable numbers for outside deployments. Treat them as an existence proof, not a guarantee of what your billing agent will do.

Who is actually using it

OpenAI named three enterprises building on Presence, and the exact verbs matter:¹

• BBVA is "exploring" AI-powered voice support for everyday banking in Mexico, and is described as a design partner refining voice experiences for financial customer service.
• SoftBank is "testing" natural Japanese-language customer conversations, with frontline teams rating the agent's Japanese highly for natural, accurate quality.
• IAG (through Retail Insurance Australia) is "exploring" timely support during high-demand events such as severe weather and natural disasters.

None of these is described as a fully live, at-scale production replacement. They are design partners and pilots — which is exactly what you would expect less than a week into a limited-availability launch. The signal is that regulated, high-stakes verticals (banking, telecom, insurance) are the target, not that they have already handed over their frontlines.

Availability, pricing, and the delivery model

Presence is available to eligible enterprise customers "as a deployed product through a limited general availability program," with deployments led by OpenAI Forward Deployed Engineers and select global systems integrators. It is explicitly "not yet available as a self-serve product."¹ OpenAI added that it will keep supporting voice customers who just want frontier-model access through the OpenAI API — Presence is the managed layer on top, not a replacement for the API.¹

Pricing is not publicly disclosed as of July 2026. OpenAI has not released list prices, geographic limits, contract terms, or the cost of the engineering and integration work that comes with a deployment; each engagement is individually scoped.² For buyers, that means the real cost question is not a per-seat or per-token rate card but the total cost of a bespoke, engineer-led rollout — the kind of number you get from an account team, not a pricing page.

Where Presence sits in the market

Presence is not the first enterprise agent platform, and it helps to be clear about that. Salesforce Agentforce, Microsoft Copilot Studio, Google's Vertex AI Agent Builder, IBM watsonx Orchestrate, ServiceNow's AI agents, and UiPath all already sell enterprise agent capabilities, most of them embedded in a broader software suite.⁴

What differentiates Presence is less the feature list and more the delivery model. The ecosystem platforms are largely self-serve builders that live inside a vendor's stack — strongest when you are already committed to that vendor, and constrained by that ecosystem's boundaries.⁴ Presence is a channel-first (voice and chat), model-native, engineer-delivered engagement that is not tied to a CRM or an office suite. It trades the self-serve convenience of a Copilot Studio for a higher-touch, more governed, more bespoke deployment. Whether that is worth it depends entirely on how mission-critical the workflow is and how much you value control over the harness.

Why it matters

Strategically, Presence is OpenAI moving up the stack. For years the enterprise pitch was raw capability: here is a model, here is an API, go build. Presence reframes the pitch as an outcome: here is a governed, deployed, continuously improving agent for a specific job, delivered by our engineers. That is a different business — closer to enterprise software and services than to a metered API — and it puts OpenAI in more direct competition with the platform vendors and the systems integrators it used to sell through.

It also puts a stake in the ground on how agents should be governed. The whole product is organized around constraint: one job per agent, least-privilege access, explicit approval gates, human escalation, simulation before launch, and evaluation after. Those are the same principles that show up whenever teams try to run agents safely, from human-in-the-loop approval patterns to the zero-trust posture enterprises are adopting against agent insider-threat risk. Presence is a bet that, for high-value production work, governance and delivery are the product — and that most enterprises would rather rent that than build it. It also sharpens the "buy vs. build" question that already hangs over every managed agent runtime.

Bottom line

OpenAI Presence turns "we have a great model" into "we will deploy and run your governed agent." It bundles policies, guardrails, approved actions, simulations, evaluations, and a Codex-driven improvement loop, then delivers the whole thing with engineers rather than a signup form.¹ The autonomous-resolution numbers are OpenAI's own and should be read as a best case, the design partners are still piloting, and the price is whatever your account team quotes. But the direction is unmistakable: OpenAI is selling the deployed, governed agent — and betting that, for mission-critical work, most enterprises would rather rent that than build it.