You do not need a budget to add safety controls to your AI agent. Several open-source tools provide production-grade safety features at no cost. This guide covers the best free options.
Full safety stack for AI agents: policy engine, content scanner (Aegis), behavioral monitor (Sentinel), approval workflows, and hash-chained audit trails. TypeScript and Python SDKs. Framework adapters for LangChain, OpenAI, and CrewAI.
pnpm add @authensor/sdk
Zero cost. Self-hosted. No per-request pricing.
Prompt injection detection, PII scanning, and credential detection. Zero runtime dependencies. Runs in-process in microseconds.
pnpm add @authensor/aegis
Prompt injection detection using multiple methods: heuristic analysis, LLM-based detection, and vector database similarity matching. Python only.
Conversational safety for chatbots. Topic control, content filtering, and dialogue management using the Colang language. By NVIDIA.
LLM output validation against schemas and quality criteria. Rich validator ecosystem. Python only.
Fine-tuned Llama model for safety classification. High accuracy on harmful content categories. Requires GPU for inference.
Real-time behavioral anomaly detection using EWMA and CUSUM statistical analysis. Tracks action rates, denial rates, and tool distribution. Zero dependencies.
Open-source LLM observability platform. Tracing, prompt management, and cost tracking. Self-hostable.
The minimum viable safety stack costs nothing:
All three run in your application process with zero infrastructure requirements. No database, no server, no external API calls. Add the control plane (PostgreSQL) when you need centralized management.
Free tools cover the core safety requirements. Consider paid tools when you need:
But start free. You can add paid tools later without replacing what you built with open-source tools.
Explore more guides on AI agent safety, prompt injection, and building secure systems.
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