OpenAI Presence: Enterprise AI Agents with Dedicated Engineers

OpenAI has launched Presence, an enterprise AI agent offering that breaks away from the traditional self-service model. Instead of selling licenses or API keys, the company deploys dedicated engineers —so-called Forward Deployed Engineers (FDE)— to implement and maintain these agents within client operations. This approach, inspired by Palantir's model, recognizes that the real bottleneck is not model capability but integration, permissions, and change management inside organizations. Presence is marketed as a project, not a packaged product. Each contract begins with a concrete use case: resolving a billing dispute, handling an insurance claim, or clearing an employee IT request. The agent is given only the knowledge and access needed for that task, and the client defines rules about when it can act autonomously, when it needs approval, and when to escalate to a human. This model directly addresses Gartner’s warning that over 40% of agentic AI projects will be canceled by 2027 due to governance failures, undefined business value, and weak operational discipline. OpenAI’s proposition includes simulations and automated graders that verify whether the agent reached the correct outcome, followed policies, used tools correctly, and escalated when required. Sessions are recorded for audit, and improvements are deployed through controlled rollouts with rollback capability. This contrasts sharply with the trend of many vendors who release dashboards and leave the customer to handle integration issues. From a business perspective, the launch of Presence confirms that deploying AI agents in production environments requires a combination of custom software, cloud infrastructure, and specialized consulting. Companies looking to adopt these systems cannot simply connect an API; they need teams that understand their processes, security, and data strategy. This is where companies like Q2BSTUDIO add value, offering AI consulting and implementation services that integrate agents with legacy systems, cloud platforms like AWS or Azure, and business intelligence tools. OpenAI’s approach of putting engineers in the field reduces technical friction but also raises questions about scalability and accountability. When the model provider also acts as the integrator, lines of responsibility for a policy error must be clearly defined in the contract. Moreover, OpenAI has not published pricing or specified the exact model powering Presence, making it hard to compare with traditional contact center solutions. The company claims the agent already resolves 75% of inbound queries on its own phone support line, but these figures have not been independently verified. The announced clients —BBVA, SoftBank, and IAG— are at early exploration stages, acting as design partners rather than large-scale implementations. This suggests Presence is still maturing. Meanwhile, OpenAI offers similar capability through three channels: ChatGPT Workspace Agents for self-service, API for developers, and Presence for managed deployments. The purchasing decision thus depends not only on technology but on available delivery capacity, which OpenAI admits is the limited resource. For enterprises wanting to advance in agentic AI without relying solely on large vendors, having a technology partner like Q2BSTUDIO enables combining custom software development with cybersecurity, cloud, and automation solutions. Experience shows that the success of an AI agent lies not in the model but in how it is integrated, governed, and continuously improved. OpenAI Presence confirms that the industry is moving toward a hybrid model where technology and professional service merge. Those who master this combination will be best positioned to capture the real value of artificial intelligence in the enterprise.