Production inference for encoder models - ColBERT, GLiNER, ColPali, embeddings etc. - as vLLM plugins for online and in-process deployment
AI-powered platform for OSINT intelligence analysis. Features archive discovery with hypothesis-driven investigation, GLiNER entity extraction, Mapbox geospatial visualization, network analysis, and document processing. Built with FastAPI, Next.js, Weaviate, and DSPy.
Python SDK for LLM guardrails with safety classification, PII detection, prompt injection defense, and grounding checks. Protect AI applications locally with zero external APIs, streaming support, and plug-and-play integration for any LLM.
Deterministic-first PII/PHI de-identification you can prove: benchmarked recall, jurisdiction policy packs, reversible tokenization, audit trail. CLI + library + GitHub Action; optional GLiNER / Gemma contextual tier.
Text preprocessing and PII anonymisation for NLP/ML. ONNX NER ensemble, language detection, stopword removal. Built for statistical ML and language models.
Comparison case study between Gliner V2 vs OpenAI Privacy filter model for PII Redaction
Benchmark harness and leaderboard for zero-shot, open-type named-entity recognition — GLiNER, GLiNER2, and LLM backends with nervaluate scoring and bootstrap CIs.
Easily configurable API & frontend providing simple access to dynamic NER models.
Self-hosted, GDPR-native AI agent for sovereign organisations. Multi-LLM, multi-channel (web, voice, mobile, Telegram, Slack), HITL on every irreversible action, native PII anonymisation pipeline. Free for personal use, commercial licence for business deployment.
Standalone RAG backend: hybrid search (pgvector + ParadeDB BM25 + LightRAG graph) with 4-mode rerank (CPU TEI + AMD gfx1151 GPU sidecars: BGE, Qwen3-Reranker 4B/8B) and GLiNER NER fast-mode. FastAPI on :5050. Bind-mount persistence.
BrainUp is an AI-driven self-improvement app created for Hack the Hill 2024. It analyzes saved Instagram reels and posts to recommend productive activities and classes based on user interests. Built with ReactJS for the frontend and a Flask API for the backend, BrainUp leverages AI models like HDBSCAN, MPnet-base v2, and Mistral for data analysis,
Leverage ModernGLiNER's capabilities using LitServe.
Fine-tuning workflows for GLiNER 2 on domain-specific entity recognition.
German-first PII redaction with checksum-validated deterministic detection and GLiNER.
Fail-closed local/cloud router for LLMs: sensitive data stays on-device. French PII detection (GLiNER + Presidio + regex), reversible pseudonymization with a burned in-memory vault, GDPR art. 32 audit log. LiteLLM + Ollama. EN/FR docs.
This project focuses on developing and fine-tuning models for medical term extraction and general named entity recognition.
🔎 NER (Named Entity Recognition) Application with Gliner 🛠️
Spoiler-aware knowledge graph for web novels — entities & relationships fenced to the chapter you've read. Local-first, GLiNER floor + optional LLM.
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