DeepRails

DeepRails is the hyper-accurate AI reliability platform built for engineering teams who demand production-grade, trustworthy AI. It acts as the definitive kill-switch for LLM hallucinations, going beyond simple detection to actively fix errors before they ever reach end-users. The platform provides real-time evaluation of AI outputs against critical guardrail metrics like factual correctness, completeness, and safety, enabling teams to ship with confidence. Designed for speed and seamless integration, DeepRails is model-agnostic and fits directly into modern development pipelines with its comprehensive API and SDKs. Its core value is delivering complete AI quality control through a unified suite of products: Defend API for real-time correction, Monitor API for observability, and Playground for testing. For developers and organizations in high-stakes domains like legal, finance, and healthcare, DeepRails eliminates the risk of unreliable AI, turning guardrails from a passive alert system into an active remediation engine that ensures every output is accurate, safe, and ready for production.

Ultra-Accurate Hallucination Detection

DeepRails sets the benchmark for precision in identifying AI errors. It evaluates outputs against a comprehensive library of guardrail metrics, scoring each for correctness, grounding, and reasoning consistency. This allows teams to distinguish genuine, harmful hallucinations from acceptable model variances with industry-leading accuracy, proven to be significantly more precise than alternatives like AWS Bedrock.

Automated Remediation & Fixing

This is the core differentiator: DeepRails doesn't just flag problems, it fixes them. The platform automatically triggers remediation workflows like "FixIt" or "ReGen" to correct detected hallucinations in real-time before the response is sent to the customer. This proactive correction engine ensures faulty outputs are resolved instantly, maintaining a seamless user experience.

Expansive & Customizable Guardrail Library

Choose from a wide array of pre-built, domain-tuned metrics or create your own. The library includes essential checks for Quality (Correctness, Completeness), Safety (PII, harmful content), and Advanced (Agentic Performance) needs. Each metric provides granular 0-100 scores, allowing for precise threshold configuration tailored to specific business objectives and risk tolerance.

Production-Ready Integration & Full Audit

Built for engineers, DeepRails integrates effortlessly with leading LLM providers and modern dev stacks via its API and SDKs. Every interaction is logged in real-time to the console, providing beautiful metrics, detailed execution traces, and complete audit logs. This offers full visibility into performance, improvement chains, and guardrail effectiveness for every AI call.

Legal & Compliance AI Assistants

Ensure every legal citation, case reference, and piece of advice is factually verifiable. DeepRails' Correctness metric validates the accuracy of AI-generated legal content, automatically fixing hallucinations about statutes or rulings. This prevents misinformation in critical documents and client communications, safeguarding against liability.

Financial Advisory & Reporting Chatbots

Guarantee the precision of financial data, investment summaries, and market analyses generated by AI. The platform evaluates outputs for factual grounding and completeness, catching and correcting erroneous figures or unsupported claims before they are delivered to customers, ensuring reliable and compliant financial guidance.

Healthcare Information & Triage Systems

Validate the safety and accuracy of AI-powered medical information, drug interaction lists, and symptom checkers. DeepRails' comprehensive safety and correctness guardrails detect and remediate hallucinations or unsafe content, protecting patient well-being and maintaining strict compliance with healthcare standards.

RAG-Powered Enterprise Knowledge Bases

Maintain the integrity of retrieval-augmented generation systems by enforcing strict context adherence. DeepRails ensures every factual claim made by the AI is directly supported by the provided source documents, automatically correcting instances where the model "makes up" information not found in the knowledge base.

How does DeepRails' accuracy compare to other solutions?

DeepRails is engineered for hyper-accuracy, consistently outperforming major platforms. Internal benchmarks show it is 45% more accurate than AWS Bedrock for correctness checks, 53% more accurate for completeness, and 51% more accurate for comprehensive safety detection, making it the most reliable choice for production guardrails.

Can DeepRails work with any LLM or AI model?

Absolutely. DeepRails is built to be completely model-agnostic. It seamlessly integrates with all major LLM providers and can evaluate, monitor, and correct outputs from any generative AI model, fitting effortlessly into your existing tech stack and development pipeline without vendor lock-in.

What does the automated "fixing" process involve?

When a hallucination is detected, DeepRails can automatically trigger predefined improvement actions. This typically involves using its "FixIt" function to correct the specific erroneous part of the output or "ReGen" to request a new, corrected response from the LLM, all in real-time before the final output is delivered to the user.

Is there a way to incorporate human feedback into the system?

Yes, DeepRails supports human-in-the-loop feedback loops. This allows for continuous improvement of model behavior over time. Human validations or corrections can be fed back into the system to refine evaluation metrics and remediation logic, ensuring the guardrails become smarter and more aligned with your specific use case.