
TrustBoost PII Sanitizer
Context-aware PII sanitization for autonomous AI agents
What it does
TrustBoost sanitizes PII from text before it reaches LLMs — emails, phone numbers, national IDs, private keys, and financial data. Context-aware: 5 modes (legal/financial/medical/code/general). Supports 8 languages including LATAM identifiers (RFC, CPF, CUIT). MCP compatible. No SDK — single POST request. 50 free sanitizations with TRIAL mode.
Does a similar job
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- ALA local-first, reversible PII scrubber for AI workflowsDec 2025 · medium.com · ▲38
Hi HN, I’m one of the maintainers of Bridge Anonymization. We built this because the existing solutions for translating sensitive user content are insufficient for many of our privacy-concious clients (Governments, Banks, Healthcare, etc.). We couldn't send PII to third-party APIs, but standard redaction destroyed the translation quality. If you scrub "John" to "[PERSON]", the translation engine loses gender context (often defaulting to masculine), which breaks grammatical agreement in languages like French or German. So we built a reversible, local-first pipeline for Node.js/Bun. Here…
ONYRI SanitizeJun 2026 · onyri-sanitize.com · ▲20Get the most out of AI without handing them your data.
- PSPII-Shield – Log Sanitization Sidecar with JSON Integrity (Go, Entropy)Feb 2026 · github.com · ▲20
What PII-Shield does: It's a K8s sidecar (or CLI tool) that pipes application logs, detects secrets using Shannon entropy (catching unknown keys like "sk-live-..." without predefined patterns), and redacts them deterministically using HMAC. Why deterministic? So that "pass123" always hashes to the same "[HIDDEN:a1b2c]", allowing QA/Devs to correlate errors without seeing the raw data. Key features: 1. JSON Integrity: It parses JSON, sanitizes values, and rebuilds it. It guarantees valid JSON output for your SIEM (ELK/Datadog). 2. Entropy Detection: Uses context-aware entropy…

- LPLocal personal data redaction for any AI toolsJun 2026 · github.com · ▲12
I built the desktop app that detects and redacts personal data (or PII) locally without sending any text to server. It supports rule-based filtering and AI model-based redaction (eg openai privacy filter). It's open source and free. Please check out the repo and https://pii-gui.vercel.app/
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, May 2026
the whole month →

Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai


- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
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Dev tools · May 2026 · github.com