DeepRails

DeepRails is a platform designed to detect and automatically correct hallucinations from large language models in real time. It sits between your application and the LLM, intercepting responses to verify factual accuracy before they reach the end user. The tool is built for developers and teams deploying LLM-powered features in production, especially where reliability and trust are critical. At its core, DeepRails uses a combination of retrieval-augmented generation (RAG) and lightweight verification models to spot statements that contradict provided context or common knowledge. When a hallucination is detected, it can automatically rewrite the response to align with facts, or flag it for human review. The platform integrates via API, making it compatible with any LLM provider or self-hosted model. What sets DeepRails apart is its focus on real-time correction rather than just alerting. Most hallucination detection tools merely flag issues, forcing developers to build fallback logic. DeepRails actively fixes outputs on the fly, reducing latency overhead to under 100ms. It also provides a dashboard for monitoring hallucination rates and model performance over time. DeepRails is best suited for customer-facing chatbots, content generation pipelines, and any scenario where inaccurate LLM output could damage trust or violate compliance. It does not replace fine-tuning or prompt engineering but serves as a safety net for production deployments.