AI Assistant
A conversational AI surface a person works with directly — answering from governed knowledge, taking approved actions, and remembering the user it serves. Copilot is the same idea embedded in a specific tool.
Production AI is a system: context, tools, permissions, traces, evals, and feedback loops around the model.
What it is
An AI assistant is the human-facing form of an agent: a chat or voice interface where someone asks in plain language and the system answers, drafts, or acts. The enterprise version differs from a consumer chatbot in what sits behind it — retrieval over the organization's own data, permission checks on every answer, and governed tools for the actions.
Why it matters
The assistant is where most people meet the AI stack, so its trustworthiness decides adoption. An assistant that cites sources, respects access rules, and declines what it doesn't know earns daily use; one that guesses gets abandoned after the first confident mistake.
How it works
A conversation surface on top of the same runtime as every workflow: retrieval grounds the answers, memory personalizes per user, tools act with approval gates, and every turn is traced. The same architecture ships as an internal tool, an embedded website widget, or a voice line.
Related resources
A language model given tools, context, and a goal — so it can take actions and check results across multiple steps, instead of producing one answer and stopping.
The pattern where an AI agent retrieves relevant context from your data before generating an answer — instead of relying only on what the model learned during training.
How an AI agent remembers the user it serves — what they said before, what they prefer, what context not to repeat — without that memory drifting the agent's behavior for everyone else.
AI agents you talk to — streaming speech-to-text, an agent turn, and streaming text-to-speech composed into a full-duplex loop where interruptions and latency are measured in milliseconds.