OpenAI Frontier
by OpenAI
Enterprise platform for building, deploying and governing AI agents that do real work.
OpenAI Frontier is an enterprise platform for building, deploying and managing production AI agents. Launched February 2026, it gives agents a shared business context spanning CRM, ERP, data warehouses and ticketing systems, then governs them the way companies govern employees, with scoped identities, permissions, onboarding and continuous evaluation. It is aimed at large organisations trying to move past isolated AI pilots.
OpenAI Frontier launched on 5 February 2026 as OpenAI's end-to-end enterprise platform for building, deploying and managing AI agents in production, and it is a deliberate move up the stack from selling model access toward owning the agent management layer. Its central idea is a shared business context: a semantic layer that maps siloed enterprise systems such as CRM, ERP, HRIS, data warehouses, ticketing tools and internal applications once, so every agent reads the same definitions instead of each project rebuilding its own integrations. Layered on that are agent identity and permissions, where each agent carries a scoped role and audit trail comparable to an employee record; a sandboxed execution environment isolating agent code and API calls; onboarding and feedback loops so agents improve from human corrections rather than being rebuilt after each failure; and evaluation tooling that makes agent quality observable instead of assumed. Analysts describe graduated autonomy, in which an operation is classified as read-only, propose-for-approval, or pre-authorised according to business risk, keeping humans in the loop on consequential actions. Frontier is explicitly open, so organisations can manage agents built outside OpenAI, and finished agents are consumed through ChatGPT, Atlas browser workflows, or embedded inside existing line-of-business applications. It entered limited availability with HP, Intuit, Oracle, State Farm, Thermo Fisher and Uber as confirmed customers and pilots at BBVA, Cisco and T-Mobile, supported by OpenAI Forward Deployed Engineers embedded on site and a Frontier Alliances partner programme spanning Accenture, BCG, Capgemini and McKinsey. Pricing is entirely unpublished and sales-led.
The CIO or Chief AI Officer at a large enterprise that already has agents scattered across business units and needs one governed control plane — identity, permissions, evaluation and audit — rather than another model subscription.
Agents that share a single definition of the business and can be granted, audited and revoked like employees, which is what lets them graduate from pilot to production work.
At a Glance
- Category
- AI Agents & Orchestration
- Pricing
- Contact for pricing
- Target Market
- CIOs, CTOs, Chief AI Officers, Enterprise Architects, Heads of Automation
- Deployment
- Cloud-only, API-based
- Founded
- 2015
- Headquarters
- San Francisco, United States
- Team Size
- 500+
- Customers
- Limited availability at launch; HP, Intuit, Oracle, State Farm, Thermo Fisher and Uber confirmed, with BBVA, Cisco and T-Mobile piloting
Key Features
- ✓Shared business context (semantic layer)
Maps CRM, ERP, warehouse and ticketing data once into business concepts, so every agent reads the same definitions instead of per-project integrations.
- ✓Agent identity and permissions
Each agent receives a scoped role, entitlements and audit trail, so access can be granted, reviewed and revoked much like an employee's.
- ✓Graduated autonomy controls
Operations are classified read-only, propose-for-approval or pre-authorised, letting risk owners keep humans in the loop on high-consequence actions.
- ✓Onboarding and feedback loops
Agents learn from human corrections and accumulated organisational knowledge rather than being redeployed from scratch after every failure.
- ✓Evaluation and optimisation tooling
Built-in evaluations make agent quality measurable and observable, which is what turns a promising pilot into something operations teams will accept.
- ✓Sandboxed execution environment
Agent code and API calls run isolated in containers so a misbehaving agent cannot cascade failures across connected business systems.
- ✓Open agent management
Manages agents built outside OpenAI as well, bringing an existing multi-framework estate under one governance layer instead of rewriting it.
- ✓Multi-surface delivery
Finished agents are consumed through ChatGPT, Atlas browser workflows, or embedded directly inside the business applications staff already use.
- ✓Forward Deployed Engineers and Frontier Alliances
OpenAI engineers embed with enterprise teams to build and run production agents, backed by Accenture, BCG, Capgemini and McKinsey delivery partnerships.
Capabilities
Use Cases
- •Customer service across several backend systems
Uber is reported to use Frontier agents for driver-side support, handling fare disputes and account issues that span multiple internal systems.
- •Insurance claims processing
State Farm is reported to apply agents to auto claims, compressing a review cycle that historically ran for days into a much shorter one.
- •Tax and financial advisory in-product
Intuit runs a TurboTax advisory agent that answers customer tax questions with the product's own data and rules held in scope.
- •Supply-chain demand forecasting
HP applies Frontier agents to demand forecasting, reconciling signals that sit across separate planning, ERP and logistics systems.
- •Agents embedded in packaged software
Oracle is building native agent capability into its ERP products, delivering agents inside applications customers already run in production.
- •Consolidating governance over an existing agent estate
A platform team registers every agent in the organisation, assigns scoped permissions, and audits precisely what each agent touched and when.
Ideal For
Best For
- ✓Consolidating agents already built across business units onto one governed control plane
- ✓Giving agents a single semantic definition of enterprise data spread across CRM, ERP and data warehouses
- ✓Customer service and claims workflows that span several systems of record
- ✓Regulated functions needing per-action approval tiers and an audit trail for every agent decision
- ✓Enterprises standardised on OpenAI models that want agents delivered inside ChatGPT and Atlas
Not Ideal For
- ✗Mid-market and SMB buyers — availability is limited, pricing is sales-led and undisclosed, and deployments lean on OpenAI Forward Deployed Engineers, so realistic entry cost is a large enterprise commitment
- ✗Teams wanting a self-serve agent SDK to start building this afternoon; AgentKit and the Responses API fit that, whereas Frontier is a governance and management layer sold through direct engagement
- ✗Organisations minimising vendor concentration: mapping your semantic layer into Frontier creates real migration cost, and analysts flag lock-in as a live risk
- ✗Creative or unstructured knowledge work — the documented wins are structured, rule-intensive, cross-system repetitive processes
Integrations
Deployment
Market & Ratings
Limited availability at launch; HP, Intuit, Oracle, State Farm, Thermo Fisher and Uber confirmed, with BBVA, Cisco and T-Mobile piloting
Market Analysis
Pros
- ✓Targets the problem enterprises actually hit after pilots — governance, identity, evaluation — rather than offering another way to call a model
- ✓The shared semantic layer means each system is integrated once and reused by every agent, removing duplicated integration work
- ✓Open to agents built elsewhere, so existing frameworks are brought under governance instead of being rebuilt
- ✓Launched with named, referenceable production customers across insurance, tax, supply chain and ERP rather than logos alone
- ✓Graduated autonomy (read-only, propose, pre-authorised) maps cleanly onto how risk owners already think about delegated authority
Cons
- ✗Agent-specific security is thinly documented — Futurum Group called the gap 'a significant hurdle to adoption', and there is no industry-standard agent security assessment framework to fall back on
- ✗No published pricing whatsoever; OpenAI's CRO declined to discuss it at launch, so budget planning and ROI calculation happen blind
- ✗Heavy dependence on Forward Deployed Engineers and consulting alliances invites a 'consultingware' outcome where the platform needs continuous outside intervention to stay useful
- ✗Mapping an enterprise semantic layer into Frontier creates substantial switching cost; analysts flag lock-in as an explicit risk
- ✗Limited availability means most enterprises simply cannot evaluate it hands-on yet, and there is no self-serve path to try it
- ✗OpenAI lacks incumbent vendors' vertical and domain depth — the Forward Deployed Engineer model implicitly concedes the market is still immature
- ✗Enterprise software practitioners on Hacker News read the positioning as OpenAI encroaching on application vendors, noting systems of record appear as 'a dotted, nearly invisible line at the bottom' of Frontier's own diagrams
Pricing
Enterprise (custom)
Contact for pricing
- ✓Custom contract scaled by agents deployed, data volume and usage
- ✓Forward Deployed Engineer support at negotiated levels
- ✓Limited availability via direct engagement with OpenAI sales
- ✓Access to Frontier Alliances delivery partners
There is no list pricing at all, and OpenAI's Chief Revenue Officer declined to discuss pricing at the launch event. Deals are custom and sales-led, scaled by the number of agents deployed, data volume, platform usage, integration complexity and how much Forward Deployed Engineer support is bundled; observers expect six- to seven-figure annual commitments. No tiers, minimums or overage terms are published, which makes budget forecasting and ROI modelling effectively impossible until you are already inside a sales cycle — a genuine barrier for anyone below large-enterprise scale.
Security & Compliance
Connect
Sources
This page was written from 8 sources, 7 on domains other than openai.com.
- 1.techcrunch.com — openai launches a way for enterprises to build and manage ai
- 2.futurumgroup.com — openai frontier close the enterprise ai opportunity gap or w
- 3.eesel.ai — openai frontier pricing
- 4.meta-intelligence.tech — insight openai frontier
- 5.cobusgreyling.medium.com — what is openai frontier b75b429465e8
- 6.hn.algolia.com — hn.algolia.com
- 7.trust.openai.com — trust.openai.com
- 8.openai.com — frontiervendor
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