Your support team's second brain — ML-powered answers from your own knowledge base, in under 25ms, without sending a single query to the cloud.
AssistSupport combines local LLM inference with a hybrid ML search pipeline to generate accurate, KB-informed IT support responses. A logistic regression intent classifier (85.7% accuracy) routes queries before a TF-IDF retriever finds candidates, and a cross-encoder reranker (ms-marco-MiniLM-L-6-v2) sharpens relevance before the response is drafted. The entire pipeline — app, sidecar, and model inference — runs on your machine. Core workspace data is encrypted at rest.
User asks: "Can I use a flash drive?"
ML Intent: POLICY detected (86% confidence)
Search finds: USB/removable media policy in 21ms
Reranker: Cross-encoder confirms top result relevance
AI drafts: "Per IT Security Policy 4.2..."
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- ML Intent Classification — Logistic regression classifier routes queries to the right search strategy before retrieval even starts
- Sub-25ms Hybrid Search — p50: 8ms, p95: 82ms across 3,500+ KB articles; TF-IDF + cross-encoder reranker pipeline
- Encrypted Local Workspace — Core SQLite database and stored secrets are protected with wrapped keys and encrypted-at-rest storage; no cloud dependency for the primary workflow
- Trust-Gated Responses — Confidence modes (answer / clarify / abstain), claim grounding map, citation-aware copy safety for low-confidence output
- Self-Improving Feedback Loop — KB gap detector surfaces repeated low-confidence topics and tracks remediation over time
- Ops-Ready Workspace — Deployment preflight, rollback flows, eval harness runs, triage clustering, and runbook sessions built in
- Node.js 20+
- pnpm 9+
- Rust toolchain (stable) + Tauri v2 prerequisites for macOS
git clone https://github.com/saagpatel/AssistSupport.git
cd AssistSupport
pnpm install
cp .env.example .envpnpm devpnpm tauri build| Layer | Technology |
|---|---|
| Desktop shell | Tauri 2 + Rust |
| Frontend | React + TypeScript + Vite |
| ML search | TF-IDF, Logistic Regression, ms-marco-MiniLM-L-6-v2 |
| Local storage | SQLite (encrypted) |
| LLM inference | Local via Ollama (optional) |
| Fonts | IBM Plex Sans, JetBrains Mono |
AssistSupport is a Tauri 2 desktop app with a Rust backend handling search, encryption, and LLM orchestration. The ML pipeline runs as a local sidecar: intent classification happens first, then candidate retrieval via TF-IDF index, then cross-encoder reranking to select the most relevant KB articles before response generation. The feedback loop writes ratings back to a local SQLite store and periodically surfaces gap analysis via the Ops workspace.
MIT