AI TOOL PROFILE
DeepRails Review: AI Hallucination Detection and Correction
- Software Development
- AI Development Platform
- Software companies
- Enterprise AI teams
- Legal tech developers
- Health tech developers
- Fintech developers
- EdTech providers
Pricing
Pricing starts at $49/month for the Basic plan. Monthly fees are available for Basic ($49), Pro ($149), and Enterprise ($499) tiers, with usage-based pricing ranging from $15 to $276 per 1K calls depending on the run mode.
At a glance
- Best for
- Software companies, Enterprise AI teams, Legal tech developers, Health tech developers, Fintech developers
- Key use cases
- Hallucination Remediation, AI Output Monitoring, High-Stakes Content Validation, RAG System Grounding
- Official website
- Visit DeepRails official website
How AI is used
DeepRails is an AI safety tool designed to detect and correct hallucinations in large language model (LLM) outputs before they reach the end user. It offers three primary tools: the Defend API for real-time correction, the Monitor API for quality tracking, and a Playground for experimentation.
The software is designed for development teams creating AI-powered products, particularly in regulated industries where incorrect information may lead to compliance or reputational risks. It uses a system of guardrail metrics to score outputs on a 0-100 scale across dimensions such as correctness and safety.
Buyers should confirm their specific accuracy needs and budget, as pricing varies based on the selected run mode and the volume of API calls. The tool also supports the creation of custom guardrail metrics for domain-specific requirements on Pro and Enterprise plans.
Key Features
Defend API
Detects low-quality or hallucinated outputs in real time and supports automatic correction using ReGen or FixIt tools.
Monitor API
Tracks quality and performance metrics across an AI stack to help identify regressions or performance drift.
Guardrail Metrics
Evaluates outputs based on Correctness, Completeness, Instruction Adherence, Context Adherence, Ground Truth Adherence, and Comprehensive Safety.
Configurable Run Modes
Offers different analysis tiers ranging from 'Super Fast' for cost-efficiency to 'Precision Max Codex' for deeper verification.
Adaptive Thresholds
Algorithms that may help auto-calibrate hallucination tolerance based on a workflow's real-world performance.
Extended AI Capabilities
Supports web search and RAG-powered file search to provide additional context during evaluation and improvement.
Use Cases
Hallucination Remediation
Identifying and fixing incorrect LLM responses before they are delivered to customers in a production environment.
AI Output Monitoring
Using the Monitor API to track the quality of AI responses and support consistency across different deployments.
High-Stakes Content Validation
Applying correctness and safety guardrails for AI tools used in medical, legal, or financial contexts.
RAG System Grounding
Using Context Adherence metrics to help ensure AI assistants use provided company documentation to answer queries.
FAQ
What is the difference between DeepRails Defend and Monitor?
- Defend is designed for real-time detection and automatic fixing of hallucinations before they reach customers, while Monitor is used to track quality and performance across an AI stack.
How does DeepRails pricing work?
- DeepRails offers a free Playground for testing and paid tiers (Basic, Pro, and Enterprise) starting at $49/month, plus usage fees based on API calls and the selected run mode.
Which industries is DeepRails designed for?
- It is designed for teams in high-accuracy fields such as finance, medical, education, and legal, where factual integrity is critical.
Source category: Software Development
Source subcategory: AI Development Platform
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