Septum
Privacy-first AI middleware with PII detection & control
What it does
AI tools are powerful — but they leak sensitive data. Septum is a privacy-first AI middleware that detects and controls PII before it reaches any model. * Automatic PII detection * Approval gate for sensitive data * Local-first processing * Works with any LLM Query your documents safely without exposing personal or sensitive information. Built for developers who need control, not blind trust.
Does the same job
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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…
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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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We’re building an open-source tool that makes it easy to expose secure, LLM-optimized APIs on top of your structured data—without manually designing endpoints or worrying about compliance. AI agents and LLM-powered applications need structured access to data, but traditional APIs and databases weren’t built with AI workloads in mind. Our tool automatically generates APIs that: - Filter out PII & sensitive data to comply with GDPR, CPRA, SOC 2, and other regulations. - Provide traceability & auditing, so AI apps aren’t black boxes, and security teams stay in control. - Optimize for AI…
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PII Detective is a web application designed to identify, classify, and protect Personally Identifiable Information (PII) in data platforms such as BigQuery and Snowflake. It leverages LLMs to identify PII column names, and with human-in-the-loop validation, uses Dynamic Data Masking Policies to easily enforce Access Control Limits (ACLs) while minimizing user friction. For comparison, GCP has a "Sensitive Data Protection" service which promises similar functionality, but it can become extremely costly since it runs hundreds of regex queries on the entire contents of the table. For…
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