AIAny
AI Infra2025
Icon for item

WeKnora

Turns enterprise documents into RAG Q&A, autonomous reasoning agents, and self-maintaining wiki pages, with multi-source ingestion, RBAC, observability, and self-hosted deployment.

Introduction

Knowledge-base tools often stop at retrieval. WeKnora tries to make documents operational: RAG answers routine questions, agents handle multi-step reasoning, and Wiki Mode maintains structured knowledge.

What Sets It Apart

It combines RAG, ReAct-style agents, MCP tools, web search, auto-wiki generation, RBAC, ownership controls, audit logs, and connectors for enterprise knowledge sources. Provider flexibility makes private deployment more realistic.

Who Should Use It

Great fit if an organization has scattered internal documents and wants self-hosted RAG plus agentic reasoning under access control. Look elsewhere for a small personal document chatbot.

More Items

Hugging Face
AI Model2026

Open-weights LLM fine-tuned for phone-based voice agents that prioritizes low latency and reliable tool/function calling. Based on NVIDIA Nemotron 3 Nano (30B total, 3.5B active), supports very long contexts (262,144 tokens) and recommends temperature=0 with thinking disabled for deployment.

GitHub
AI Infra2025

Measures generative AI inference performance with token-level metrics (TTFT, inter-token latency), latency, and throughput under realistic traffic patterns. Provides a multiprocess engine, real-time TUI dashboard, extensible plugins, and integrations for telemetry and result uploads, aimed at inference benchmarking and capacity planning.

GitHub
AI Agent2026

A curated collection of production-ready Agent Skills that turn tasks—presentation production, image generation, local KB retrieval, article assembly, and web-design—into agent-loadable skill folders. Uses a SKILL.md contract, supports multiple agent runtimes (Claude Code, Cursor, Codex), and offers modular install paths with pinned release zips.