TeqEngine delivered agent platform engineering across backend AI, APIs and infrastructure for a platform serving a unicorn startup and Fortune 500 companies in high-volume operation.
We built the systems behind its agent capabilities: more than 50 MCP tools, model integrations with Anthropic, OpenAI and Google, semantic search, and APIs for structured content. That foundation lets agents find information, act on it and support interactive experiences inside compatible AI clients.
Backend AI and model integrations
We integrated support for models from Anthropic, OpenAI and Google into the AI backend. This gives the platform model choice for its agent features, alongside the tools and retrieval capabilities that let agents work with business information.
APIs and 50+ MCP tools built
We built content APIs and more than 50 tools using the Model Context Protocol (MCP). The work covered discovering content types, searching for existing information, and creating and updating entries.
These APIs and tools make structured content available to developers and agents. An agent workflow can retrieve information, use it to create a new entry, and update existing content through the platform.
Retrieval and interactive agent experiences
We built semantic search for retrieving relevant information from the platform's content. It supports agent workflows that start with existing business information, such as finding material to use when creating or updating an entry.
The platform also supports MCP Apps: interactive interfaces within compatible AI clients. Our backend and MCP work supports those experiences, connecting agent interactions to the platform's content and actions.
Platform architecture and infrastructure
TeqEngine led the architecture, development and delivery of the AI backend, APIs and infrastructure supporting these capabilities. The work connected model integrations, retrieval and agent actions into a platform used by enterprise customers.