UtopikAI brought company information and multiple AI models into a shared workspace. Ego Eimi worked with Jimit Raval on the platform engineering behind connectors, retrieval, assistants and generation tools.
A useful business assistant needs access to the documents and tools where the answer lives. Without those connections, people copy material between applications and lose the relationship between an answer and its source.
Different teams also need different context and permissions. The platform had to connect multiple models and business data while giving departments an appropriate workspace.
The application routed tasks across GPT, Claude, Gemini, Mistral and Llama. Business-tool connectors supplied information to a retrieval pipeline, grounding answers in company documents.
Department-specific assistants, a no-code agent builder and a media Studio extended that foundation. Role-based access, audit logs and deployment configurations supported different organizational requirements.
Models, retrieval and team workspaces. The delivery section explains the workflow demonstrated here.
The platform joined models, company context and team workflows in one application. Retrieval and access control became shared capabilities that could support several kinds of assistant and generation task.
The owner of a connected AI workspace must understand connector permissions, retrieval freshness and model routing. Adding a new source can change who can discover information. A clear operating record documents those boundaries and how they are tested when the platform changes.
Project contribution: Jimit Raval. The scope described above identifies the work behind this case.
Editorial review: Ego Eimi · Updated September 6, 2026 · About the team
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