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@Inferensys

Inference Systems

Inference Systems designs AI systems around your data, tools, and operations, from AI data retrieval and RAG to AI agents, workflow automation, enterprise AI go

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  1. ai-evals-scorecard ai-evals-scorecard Public

    Score model outputs against explicit rubrics with an Azure-backed judge, deterministic aggregation, and diffable JSON reports.

    Python

  2. browser-task-copilot browser-task-copilot Public

    Guarded browser task control plane with Azure-backed action planning, YAML policy evaluation, approval checkpoints, and replay timelines.

    Python

  3. crawl-to-knowledge-pipeline crawl-to-knowledge-pipeline Public

    Manifest-driven crawl reference for canonicalization, freshness diffs, and retrieval-ready knowledge exports.

    Python

  4. multimodal-doc-intake-kit multimodal-doc-intake-kit Public

    Schema-first document ingestion reference with layout-aware normalization, review queues, and provenance-preserving chunks.

    Python

  5. product-ai-actions-kit product-ai-actions-kit Public

    Reference patterns for in-product AI assistants with typed actions, approval gates, and append-only audit trails.

    Python

  6. realtime-voice-agent-starter realtime-voice-agent-starter Public

    Low-latency voice agent starter focused on call-state transitions, barge-in policy, handoff contracts, and post-call events.

    TypeScript

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