Map planners, tool execution, retrieval, and UI embedding for in-app copilots
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Design full-stack LLM applications with routing, retrieval, tooling, and safety layers
Add safety layers to LLMs with content filters, policies, approvals, and audit logs
Instrument LLMs and ML models with tracing, metrics, drift detection, and user feedback
Common questions about ai copilot architecture generator
Gate tool calls with policy checks, approvals, and dry-run modes. Log all actions with user attribution.
Combine user state, active document, retrieved knowledge, and recent interactions. Keep summaries for long sessions.
Use personas with different tools and permissions. Route tasks based on role-specific policies and datasets.
Track task completion, edits accepted, time saved, safety blocks, and user satisfaction. Run A/B tests on prompts.
Embed as side panel or inline actions with streaming responses and quick actions for tool outputs.
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