MeetUma (Uma)

MeetUma (Uma) represents the 2026 evolution of the personal AI agent, moving beyond basic chat interfaces into a deeply integrated 'Knowledge Layer' for professionals. Technically, the platform utilizes Retrieval-Augmented Generation (RAG) paired with a vector-indexed 'Personal Knowledge Graph' that ingests data from Google Workspace, Microsoft 365, Slack, and Notion. Unlike standard LLMs that hallucinate personal facts, Uma maintains a persistent memory of the user's professional ecosystem, allowing it to perform high-reasoning tasks like cross-referencing a PDF in an email with a project timeline in Notion. The 2026 architecture leverages small language models (SLMs) for on-device privacy-sensitive tasks while delegating complex reasoning to larger frontier models. This hybrid approach ensures sub-second latency for information retrieval. Positioned as a 'Chief of Staff,' it focuses on context-aware task execution, such as drafting follow-ups that reference specific past interactions across multiple platforms, effectively solving the 'fragmented data' problem that plagues modern knowledge workers.