Contextual AI: Powering Enterprise-Grade AI Agents with Grounded Knowledge

Contextual AI is a cutting-edge enterprise platform engineered to build highly accurate, knowledge-intensive AI agents by grounding them in organizational data. Designed by pioneers in RAG (Retrieval-Augmented Generation), it leverages RAG 2.0 technology to jointly optimize retrieval and generation, drastically reducing hallucinations and ensuring reliable, factually sound outputs. The platform is ideal for professionals in regulated industries like finance, legal, and technology who need scalable, secure, and compliant AI solutions. With modular APIs, a no-code agent builder, and pre-built templates, Contextual AI enables seamless integration into existing workflows while supporting both unstructured and structured data—including complex documents, charts, tables, and multimodal content. It offers enterprise-grade security with SOC 2 Type II and HIPAA compliance, end-to-end encryption, role-based access control, SSO, and advanced threat protection.

Key Features:

• RAG 2.0 Architecture: Jointly optimizes retrieval and generation components for higher accuracy and reduced hallucinations.
• Multimodal Retrieval & Parsing: Extracts and understands text, images, charts, tables, and technical diagrams with document hierarchy inference and positional metadata.
• Instruction-Following Reranker API: Uses natural language to dynamically prioritize retrieved content based on recency, source, document type, and metadata.
• Grounded Generation API: Delivers the world’s most grounded LLM outputs with in-line attributions and precise citations.
• LMUnit API: Enables natural language-based evaluation of LLM responses for conciseness, precision, equivalence, and groundedness.
• No-Code Agent Builder: Drag-and-drop interface with pre-built templates for knowledge-intensive workloads.
• Continuous & Automated Data Ingestion: Ensures data freshness with real-time updates across enterprise sources.
• Flexible Deployment Options: Fully managed SaaS, within customer’s VPC, or on-premises for maximum control and security.
• Enterprise Security & Compliance: SOC 2 Type II and HIPAA certified; includes end-to-end encryption, SAML/SSO, RBAC, 2FA, and GRC automation.
• Advanced Evaluation Tools: Built-in groundedness scoring and real-world evaluation for measuring response accuracy.
• Fine-Tuning & Alignment Tools: Robust customization options for retrieval, generation, and safety guardrails.
• Integration with Popular SaaS Platforms: Supports Slack, Google Drive, GitHub, and SharePoint out of the box.
• Mixture-of-Retrievers Approach: Enhances accuracy through iterative retrieval and reasoning chains.
• Uptime SLAs & Elastic Scalability: Ensures high availability and performance under heavy loads.
• Developer-Friendly SDKs: Available in Python, JavaScript, and TypeScript for full lifecycle development.
• Active Retrieval & Test-Time Reasoning: Enables complex, multi-step reasoning over vast enterprise data.

Pricing: Contextual AI offers a freemium model with free access to the end-to-end platform until June 10, 2025, and $25 in free credits for component APIs. The first 500+ pages in Standard mode are also free. Beyond that, pricing is usage-based with options for on-demand and provisioned throughput models. On-demand pricing includes $0.05 per query (based on tokens), $48.50 per 1,000 pages for ingestion, and per-token rates for Rerank ($0.12 per 1M tokens input), Generate ($3 per 1M input, $15 per 1M output), and LMUnit ($3 per 1M tokens input). Provisioned throughput offers monthly commitments with added features like SAML/SSO, RBAC, usage analytics, and dedicated VPC deployment.

Conclusion: Contextual AI stands at the forefront of enterprise AI innovation, delivering a powerful, secure, and highly accurate platform for building trustworthy, grounded AI agents—perfect for organizations that demand precision, compliance, and scalability in their AI workflows.