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Universal Context Engine (UCE)

Local-first, privacy-centric personal assistant for macOS. Integrates Slack, Jira, Gmail, and arbitrary data sources via a generic connector framework. Automates task extraction and draft proposal through a Ghost Drafting workflow. All inferences default to local execution; cloud escalation is restricted and PII-redacted.

Specifications

Document Description
UCE-Technical-Specifications-v1.1.md Core spec: unified ingestion, air-gapping, relationship awareness, task extraction, Ghost Drafting
UCE-Technical-Specifications-v1.2-addendum.md v1.2 additions: generic connector framework, PII-aware cloud LLM routing, on-demand UI generation, cloud search integration
UCE-Gap-Analysis.md Gap analysis against existing Personal Assistant codebase — what exists, what's partial, what's absent, prioritized refactoring plan
EVALUATION-FINDINGS.md Evaluation of v1.0 spec: 15 issues identified and resolved in v1.1
CHANGES-SUMMARY.md Diff summary: v1.0 → v1.1

Core Design Principles

  • Local-first: All inference defaults to on-device (Apple Foundation Models + Phi-4/Llama via MLX). Cloud escalation requires explicit user confirmation.
  • Privacy by partition: Data tagged [Work], [Personal], or [Shared] at ingestion. Separate LanceDB indexes per partition. [Personal] never leaves the device.
  • PII redaction before cloud: Any text sent to a cloud LLM is redacted via PIIRedactor (names, emails, phones, addresses replaced with consistent tokens; de-anonymized in response).
  • Connector-agnostic ingestion: Any data source implements a single Connector protocol. Cross-cutting concerns (retry, dedup, auth, tagging) handled by ConnectorHost — connector authors write source-specific logic only.
  • Human in the loop: Ghost Drafts require explicit approve/edit/reject before posting to any source system.

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Universal Context Engine — local-first, privacy-centric personal assistant specifications

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