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DeepRails
A platform that detects and automatically corrects LLM hallucinations in real time using a proprietary evaluation engine.

About DeepRails
DeepRails is an AI reliability platform designed to detect, score, and automatically correct hallucinations, safety violations, and drift in production LLMs. It uses a proprietary Multimodal Partitioned Evaluation (MPE) engine and real-time APIs (Evaluate, Monitor, Defend) to ensure outputs remain accurate and compliant. The platform provides model-agnostic guardrails, enabling teams to add reliability layers without modifying underlying models. It offers audit-ready monitoring, alerts, and a Hallucination‑Safe™ certification for verified outputs. Teams deploy it in minutes to reduce costs, minimize churn, and maintain high reliability across applications. DeepRails is particularly useful for organizations relying on LLMs in customer-facing or high-stakes environments where accuracy is critical.
Key features
- Detects LLM hallucinations in real time
- Automatically corrects identified hallucinations
- Multimodal Partitioned Evaluation (MPE) engine
- Real-time APIs for evaluation, monitoring, and defense
- Model-agnostic guardrails for any LLM
- Audit-ready monitoring and alerts
- Hallucination‑Safe™ certification for outputs
- Drift detection for ongoing reliability
- Quick deployment in minutes
- Reduces costs and churn from errors
Use cases
- Ensuring accuracy in customer-facing AI applications
- Monitoring and correcting hallucinations in production LLMs
- Certifying outputs for compliance or safety-critical use cases
Pros
- Provides model-agnostic guardrails for LLMs without requiring model modifications
- Offers real-time monitoring and automated correction of hallucinations, safety violations, and drift
- Delivers audit-ready monitoring, alerts, and compliance documentation
- Includes a Hallucination‑Safe™ certification for verified outputs
- Designed for rapid deployment with minimal setup time
Cons
- Limited public information on pricing models or specific feature availability
- May require integration adjustments for existing LLM workflows
- Certification process could introduce additional operational steps
Frequently asked questions about DeepRails
What does DeepRails do?
DeepRails is an AI reliability platform that detects, scores, and automatically corrects hallucinations, safety violations, and drift in production LLMs using a proprietary evaluation engine and real-time APIs.
Who is DeepRails designed for?
The platform is designed for organizations relying on LLMs in customer-facing or high-stakes environments where accuracy and compliance are critical.
How does DeepRails ensure reliability?
It uses a Multimodal Partitioned Evaluation (MPE) engine and real-time APIs (Evaluate, Monitor, Defend) to provide model-agnostic guardrails and automated corrections.
Does DeepRails require modifying the underlying LLM?
No, DeepRails operates as a model-agnostic layer, allowing teams to add reliability without altering the original model.
What kind of monitoring does DeepRails provide?
The platform offers audit-ready monitoring, alerts, and compliance documentation to track and verify LLM outputs.
How can I get started with DeepRails?
Teams can deploy DeepRails in minutes, though specific onboarding steps would depend on the chosen plan or consulting engagement.
DeepRails traffic & engagement
deeprails.com · third-party estimates from Similarweb
Traffic trend
Last 4 months · grows by one month every month
- Jun 20262.4K
- Jul 20261.8K−24.3%
- Aug 20262.1K+16.3%
- Sep 2026842−59.4%
Where visitors come from
Share of visits by channel
Top countries
Share of visits · estimated visits
Compared with similar tools
Coding & Development · Sep 2026
Traffic figures are third-party estimates, good for scale and trends; they can differ from a company's own numbers. Updated monthly.