Contextual AI

Contextual AI is the fastest way to build accurate scalable RAG agents for enterprise knowledge integration.

What is

Contextual AI

?

Contextual AI is an end-to-end developer platform for building Retrieval-Augmented Generation (RAG) AI agents that specializes in transforming complex enterprise documents into actionable knowledge. The platform offers Contextual RAG Agent technology with out-of-the-box accuracy and fast deployment capabilities. With enterprise-grade security and flexible deployment options including fully managed SaaS, VPC, and on-premises installations, Contextual AI serves financial services, technology, and legal industries. Backed by prominent investors including Bain Capital Ventures, Greycroft, and Lightspeed Venture Partners, the platform integrates with major cloud providers and offers specialized document understanding for complex enterprise use cases.

Key Features
  • Contextual RAG Agent for knowledge retrieval
  • Document Understanding for complex enterprise docs
  • Specialization Engine for domain-specific models
  • Agent Templates for rapid deployment
  • Multi-deployment options (SaaS, VPC, on-premises)
  • Enterprise security and compliance
  • Cloud integrations (AWS, GCP, Azure)
  • Real-time processing capabilities
Pricing
  • Start for free: Available trial option
  • Enterprise pricing: Custom solutions
  • Contact for detailed pricing information
Pros:
  • Out-of-the-box accuracy for enterprise documents
  • Fast deployment with minimal setup
  • Flexible deployment options for security needs
  • Strong investor backing ensuring continued development
  • Enterprise focus with proven industry partnerships
  • Specialized for RAG use cases
Cons:
  • Out-of-the-box accuracy for enterprise documents
  • Fast deployment with minimal setup
  • Flexible deployment options for security needs
  • Strong investor backing ensuring continued development
  • Enterprise focus with proven industry partnerships
  • Specialized for RAG use cases
Who is it for?
  • Financial services firms processing reports
  • Technology and engineering teams with complex documentation
  • Legal and professional services handling compliance
  • Enterprise developers building RAG applications
  • Data teams managing knowledge systems
  • Compliance officers tracking regulatory documents
Best use cases
  • Financial report analysis and processing
  • Engineering documentation search and retrieval
  • Expert call transcript synthesis
  • Regulatory compliance document tracking
  • Knowledge base creation and management
  • Enterprise document understanding
API Integrations
  • AWS integration and partnership
  • Google Cloud Platform support
  • Snowflake data warehouse connection
Security
  • Enterprise-grade security for sensitive documents
  • Multiple deployment options for compliance
  • Data protection and privacy controls
Implementation
  • Implementation typically takes 1-2 weeks for basic RAG deployment, with 2-4 weeks for enterprise integration including custom document processing and security configurations.
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