# OpenAI Frontier Enterprise platform for building and managing AI agents at scale ## About OpenAI Frontier OpenAI Frontier is built for large enterprises, with HP, Intuit, Oracle, State Farm, Thermo Fisher, and Uber named as launch customers. It requires custom contracts, Forward Deployed Engineers, and months of enterprise onboarding. Sistava delivers the same agent workforce concept but self-serve, instant, and accessible to businesses of any size without needing an OpenAI account team. ## Platform details - Pricing: Custom enterprise only. No public pricing. Fortune 500 focused. Contact sales. - Founded: Launched February 2026 (OpenAI founded 2015) - Funding: OpenAI: $180B+ raised, including a $122B round in early 2026 backed by Amazon ($50B), Nvidia ($30B), and SoftBank ($30B), at an $852B valuation. - Last reviewed: 2026-08-13 ## Official website - [Visit OpenAI Frontier](https://openai.com) ## What does OpenAI Frontier actually do? OpenAI Frontier is the agent deployment platform OpenAI launched in February 2026 for enterprises running autonomous AI agents at scale. It is separate from ChatGPT Enterprise: Enterprise is a chat productivity product, while Frontier is the infrastructure layer for multi-step agents that take actions, coordinate models, and operate with minimal human input. Customers typically use it alongside a Forward Deployed Engineer team. Frontier focuses on orchestration, evaluation, observability, and governance for agents built on OpenAI's frontier models. Tracing is built in and captures every LLM generation, tool call, and handoff, with export to more than 20 observability platforms, and the platform speaks MCP, with OpenAI-maintained Connectors described as MCP wrappers. It targets companies that already have ML platform teams and want to ship agents into core workflows like research, claims, underwriting, or back-office processing. The platform handles agent versioning, tool registration, and policy controls that a single ChatGPT seat cannot. For most small teams, Frontier is overkill. It exists to solve a problem that does not really exist below a few hundred employees: how to deploy hundreds of agents safely across many departments. Sistava sits at the opposite end. It ships pre-built AI employees with built-in tools, prompts, memory, and a chat surface that a solo founder can hire in minutes without engineering support. ## How much does OpenAI Frontier cost? OpenAI has not publicly disclosed Frontier pricing, so everything in this section is industry reporting rather than a published rate. Deals are negotiated directly with sales and reportedly scale by number of agents, data volume, API consumption, deployment environment, and the level of Forward Deployed Engineer support included. Reporting puts pricing well above ChatGPT Enterprise, which is itself described as starting around 60 dollars per user per month with a 150-seat minimum and an annual commit. The practical floor for a serious Frontier engagement is reported at six figures per year before any internal engineering effort. Companies also need to budget for the API tokens consumed by every agent run, plus the integration work to connect Frontier agents to internal systems and data lakes. What is verifiable from the public site is simpler: no self-serve tier and no published price list. Sistava is the inverse. The product is bootstrapped, pricing is published, and a solo founder can sign up, hire a marketing or sales AI employee, and see real output the same afternoon. There is no minimum seat count and no enterprise procurement cycle. For teams under fifty people, that gap matters more than the underlying model strength. ## When does OpenAI Frontier beat the alternatives? Frontier wins when the customer is already a major OpenAI account, has hundreds of agents in production or planned, and needs a single governance plane across them. The Forward Deployed Engineer model is a real differentiator: OpenAI assigns engineers who help shape the agents around proprietary data and workflows. Few vendors offer that level of co-development. The launch customer list is HP, Intuit, Oracle, State Farm, Thermo Fisher, and Uber, with BBVA, Cisco, and T-Mobile reported as pilots, so the buyer profile is consistently large enterprise, not mid-market. It also wins when reasoning quality on the latest GPT-5 series is the binding constraint. Frontier agents get first access to model upgrades, longer context windows, and multimodal features that take months to filter into third-party platforms. For research, scientific, or analytical workloads where model strength is the whole game, that head start is worth the premium. Where Frontier loses is anything below the enterprise floor. Solo founders, micro-agencies, and small SaaS companies do not need agent orchestration at scale. They need one or two AI employees that can actually finish a task. Sistava is built for that level and only that level, with no overhead from a platform designed for Fortune 500 deployments. ## Where does OpenAI Frontier fall short for small teams? Frontier is not designed for small teams and the gap shows immediately. There is no self-serve signup, no published price list, no free trial, and no way to evaluate the product without a sales motion. A founder evaluating tools on a Friday night cannot try it at all. By Monday morning a Sistava user has already shipped a campaign brief, a sales sequence, or a backlog of cold outreach. The platform also assumes the customer brings their own engineers. Frontier provides primitives: agent runtime, evaluation, observability, tool registration. The customer still wires those primitives into business workflows. For a five-person company, that is the entire problem. They want the AI employee, not the platform to build it on. Sistava covers the layers Frontier leaves to the customer. Prompts, skills, memory, browser tools, integrations, and a chat surface all ship in the product. The trade-off is conscious: less customization at the model orchestration layer, but a working AI workforce on day one rather than a multi-quarter implementation project. ## How does OpenAI Frontier handle enterprise lock-in? Frontier centralizes the customer on OpenAI's stack across model inference, agent runtime, evaluation tooling, and observability. That is the point of the product. Once agents are built against Frontier primitives with Forward Deployed Engineer support, migrating to another model provider becomes a multi-quarter rewrite. Lock-in is the deliberate trade-off for the head start on new model capabilities. For large enterprises that have already standardized on OpenAI, this concentration is acceptable and often preferred. Procurement, security review, and vendor management all simplify when one provider covers the whole stack. The Forward Deployed Engineer relationship also makes switching costs feel less risky in practice. Sistava takes a different stance. AI employees can route to different model providers based on the task, the product is hosted independently, and customers are not locked into a single foundation model vendor. For a small team that wants flexibility as the model landscape shifts every few months, that matters more than the depth of a single enterprise integration. ## Comparison - [Compare OpenAI Frontier with Sistava](/en/compare/enterprise/openai-frontier) — See the two platforms side by side when you are ready to evaluate them.