Privacy
- AI/ML Workshop
—
ml
,
onboarding
,
privacy
A carefully curated set of practical, highly reproducible machine learning examples (PyTorch, Hugging Face, NumPy) featuring MPS-aware benchmarks and rigorous experiment hygiene for local hardware.
- Mailprune
—
data-pipelines
,
monitoring
,
networking
and +1 more
A highly effective, local-first email auditing and automated cleanup tool designed to definitively identify noisy senders and deliver actionable, strictly privacy-preserving recommendations.
- Privacy & Agents
—
privacy
Privacy-first design rules for autonomous AI agents; establishing local-first execution defaults, strict data minimization and redaction, explicit user consent flows, and transparent, auditable action logs.
- Privacy-Preserving Federated Learning Platform
—
algorithms
,
distributed-systems
,
ml
and +1 more
A secure platform design for advanced federated learning pipelines; training models directly across edge devices without sharing raw telemetry, utilizing secure local aggregation and robust privacy safeguards.
- Ragchain
—
ml
,
privacy
,
retrieval
A comprehensive local RAG stack (ChromaDB + Ollama) designed for strictly private, reproducible retrieval and LLM inference; heavily focusing on hybrid retrieval strategies and index versioning.
- Search & Retrieval Engine
—
algorithms
,
monitoring
,
privacy
and +1 more
A high-performance search and retrieval engine architecture designed for extensive document and media collections; strictly ensuring low-latency ranking and horizontally scalable inverted indexing.