Developers, AI agent builders, product teams, and technical buyers integrating AYA into tools and workflows.
Orient developers to AYA APIs, connectors, docs, authentication, and install routes.
Twin Engine APIs
AYA exposes API surfaces for resolving panels, running quick pulses, creating concept tests, submitting research briefs, and checking research job status. Typical endpoints live under /v1 and return JSON responses designed for product integrations and AI agents.
AI connectors
Public connector routes support AI-native workflows in external assistants, including Claude MCP and ChatGPT Actions setup paths.
Production surfaces
Developers use docs, guides, install pages, and authenticated console routes to understand integration patterns, authorization headers, job lifecycle, webhook payloads, example requests, error shapes, rate limits, and OpenAPI-oriented reference material.
Developer evaluation path
Technical buyers should use the developer pages to understand the public integration surface, authentication model, connector routes, API concepts, and documentation map before building against AYA. Private consoles and account-specific tools remain outside the crawlable marketing surface.
AI agent context
These pages are written so coding assistants and retrieval agents can distinguish AYA APIs, MCP connectors, ChatGPT Actions, install guides, and reference material from the general product marketing pages.
Implementation boundary
A useful developer journey starts with the public docs, then moves into authenticated workspace setup only when the buyer is ready. Public documentation should explain what an integration can do, which workflows are available, how authentication is approached, how job status is handled, and where examples or reference material sit. It should not expose private customer data, secret tokens, or account-specific console routes to search engines.