Description for Contextual AI
Contextual AI is a platform with enterprise-grade capabilities that enables the development of Retrieval-Augmented Generation (RAG) agents that are both extremely accurate and scalable. It facilitates the effortless integration of AI systems into intricate enterprise data by providing developers and businesses with modular components, rapid deployment, and RAG 2.0 optimisation.
Features of Contextual AI:
- End-to-End RAG Orchestration: A unified platform that includes state-of-the-art components for retrieval, generation, and evaluation.
- Contextual RAG Agent: Highly accurate outputs are achieved through joint optimisation of retrieval and generation, which reduces compounding errors.
- Contextual Document Understanding: Extracts actionable insights from large, complex enterprise documents.
- Specialisation Engine: Post-training techniques for fine-tuning and feedback alignment to your domain.
- Agent Templates: Agent frameworks that are pre-built and can be customised to facilitate rapid deployment across a variety of use cases.
- Enterprise Security & Controls: Designed to comply with regulatory requirements through auditability and granular access control.
- Deployment Options with Flexibility: Deploy on on-premises infrastructure, in your VPC, or on a fully managed SaaS.
- Expert Support: Access to ML experts for production-ready deployments and optimisation.
Use Cases for Contextual AI
- Financial Services: Automate the analysis of financial reports, compliance monitoring, and market research.
- Technology & Engineering: Facilitate comprehensive searches of technical specifications, code repositories, and documentation.
- Legal & Professional Services: Extract insights from legal documents, transcripts, and policy manuals.
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