LockLLM
All-in-One AI Security
LockLLM launched on February 20, 2026 with 3 votes, #3,486 of 16,627 launches that month and more than 50% of that year's launches.
What it does
LockLLM is the security layer purpose-built for large language model applications. It monitors prompts and responses in real time, blocking prompt injection, preventing data leakage, and enforcing customizable guardrails. With seamless integration and centralized logging, LockLLM enables teams to scale AI confidently while maintaining compliance, control, and brand integrity.
Secure your LLM apps and cut AI costs with real-time threat detection, smart model routing, custom policies, prompt compression and PII redaction
Secure AI gateway with built-in threat detection, content moderation, privacy redaction, smart routing, and prompt compression. Access any AI model, protect your apps, prevent abuse, and reduce costs - all through one API. LockLLM sits in front of your agents and flags risky inputs in real time. Decide what gets through, what gets blocked, and what needs a safer path. No need to build injection detection, custom policies, or routing logic yourself. LockLLM provides everything you need in one platform, so you can focus on building your AI product. Risky inputs often look normal at first. We flag threats, policy violations, and sensitive data before they reach your model. LockLLM scans…from lockllm.com
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AnythingLLM – Open-Source, All-in-One Desktop AI Assistant2024 · github.com · ▲368Hey HN! This is Tim from AnythingLLM (https://github.com/Mintplex-Labs/anything-llm). AnythingLLM is an open-source desktop assistant that brings together RAG (Retrieval-Augmented Generation), agents, embeddings, vector databases, and more—all in one seamless package. We built AnythingLLM over the last year iterating and iterating from user feedback. Our primary mission is to enable people with a layperson understanding of AI to be able to use AI with little to no setup for either themselves, their jobs, or just to try out using AI as an assistant but with *privacy by…




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