DeepRails

About DeepRails

DeepRails is your essential AI reliability platform, designed to help developers and teams build trustworthy, production-ready AI systems. As large language models (LLMs) become part of real-world applications, a major challenge is their tendency to "hallucinate" or generate incorrect, misleading, or ungrounded information. DeepRails tackles this head-on as the only guardrails solution that doesn't just find these errors but actively fixes them. It acts like a quality control checkpoint for your AI, evaluating every output for factual correctness, grounding in source material, and logical consistency. This allows you to catch mistakes before they reach your users, giving you the confidence to ship AI features you can truly stand behind. Built for modern development pipelines, DeepRails is model-agnostic, integrates seamlessly with leading LLM providers, and offers automated remediation, custom metrics, and continuous improvement loops to ensure your AI behaves reliably over time.

Features of DeepRails

Defend API - Real-Time Correction Engine

The Defend API is your frontline defense against AI errors. It acts as a real-time filter and corrector for your LLM's outputs. You simply send the AI's response to the API, and it automatically evaluates it against your configured guardrails for correctness and safety. If a problem like a hallucination is detected, it can trigger automated "FixIt" or "ReGen" actions to correct the output or generate a new, improved one before it's ever sent to your customer, ensuring only high-quality responses get through.

Ultra-Accurate Hallucination Detection

DeepRails goes beyond simple keyword flagging to provide hyper-accurate identification of AI mistakes. Its sophisticated evaluation engine distinguishes between true factual errors, acceptable variations in model response, and ungrounded assertions. This high precision means you spend less time on false alarms and more time fixing real issues, making your quality control process both effective and efficient.

Configurable Workflows & Run Modes

You have full control over how DeepRails operates. You can configure custom Workflows that define your specific quality metrics—like correctness, completeness, and safety—and set the tolerance thresholds for each. Furthermore, you can choose from five powerful "Run Modes," from "Fast" for low-cost, high-speed checks to "Precision Max Codex" for the deepest, most thorough verification. This lets you perfectly balance accuracy, speed, and cost for every use case.

Centralized Console with Full Audit Trails

The DeepRails Console gives you complete visibility into your AI's performance. Every interaction processed by the Defend API is logged in real-time. You can view beautiful dashboards tracking key metrics, drill down into detailed traces of any individual AI run, and see the complete "improvement chain" showing how an output was evaluated and fixed. This provides invaluable analytics for improvement and full audit compliance.

Use Cases of DeepRails

Customer Support Chatbots

Ensure your support AI provides accurate, helpful information every time. DeepRails can verify that instructions for resetting a password, troubleshooting steps, or policy details are factually correct and grounded in your knowledge base, preventing the chatbot from inventing solutions that frustrate users and increase support tickets.

Legal and Compliance Document Analysis

In high-stakes fields like law, accuracy is non-negotiable. DeepRails can scrutinize AI-generated case summaries, contract clauses, or compliance checklists. It checks for hallucinated legal precedents, incorrect citations, or unsound reasoning, safeguarding against errors that could have serious professional consequences.

Educational Content and Tutoring AIs

Create reliable learning assistants. Whether an AI is explaining a complex math concept or summarizing a historical event, DeepRails ensures the information is factually sound and logically consistent. This protects students from learning incorrect information and builds trust in educational technology tools.

Financial and Insurance Advisory Tools

Build trustworthy financial assistants. DeepRails can guard AI outputs that explain insurance policy terms, provide investment summaries, or calculate estimated returns. By verifying numerical accuracy and grounding advice in official documentation, it prevents the AI from giving misleading financial information that could erode customer trust.

Frequently Asked Questions

What makes DeepRails different from other AI evaluation tools?

Most tools only detect potential problems and flag them for a human to review. DeepRails is unique because it provides both best-in-class detection AND automated remediation. It doesn't just tell you something is wrong; it can actively fix the hallucination or generate a new, correct response in real-time, acting as an automated correction layer in your production pipeline.

How do I integrate DeepRails into my existing application?

Integration is straightforward for developers. DeepRails provides simple SDKs and a clean REST API. After getting your API key, you can wrap your calls to your LLM (like OpenAI or Anthropic) with a call to the DeepRails Defend API. You send your model's output to DeepRails for evaluation and correction, and then receive the verified (or improved) response to send to your user. Detailed guides are available in the API Docs.

Can I customize what DeepRails checks for?

Absolutely! This is a core strength of DeepRails. You configure custom "Workflows" where you define the specific evaluation metrics important to your business, such as factual correctness, completeness of answer, safety, or custom criteria. You also set the score thresholds that determine what passes or fails, giving you total control over your AI's quality standards.

What are "Run Modes" and which one should I choose?

Run Modes let you choose the balance between evaluation speed, depth, and cost. For example, use "Fast" mode for high-volume, low-risk chats where speed is critical. For high-stakes outputs in legal or medical contexts, switch to "Precision Max" or "Precision Max Codex" for the most thorough verification. You can experiment in the Playground and even use different modes for different parts of your application.