.svg)
H2O.ai is an enterprise AI platform that converges generative AI and predictive AI into a unified solution purpose-built for private, protected data. At its core is h2oGPTe, a multi-agent generative AI platform offering advanced RAG, autonomous agentic workflows, multimodal analysis, model risk management, and intelligent model routing — all deployable on-premises or in air-gapped environments.
The platform supports the full AI lifecycle: from AutoML-driven predictive modeling with H2O Driverless AI, to no-code LLM fine-tuning with H2O LLM Studio, to deployment and monitoring via H2O MLOps. h2oGPTe enables grounded query responses from secure, private document repositories, knowledge bases, and databases using advanced vector embeddings and proprietary hallucination-mitigation techniques.
Enterprise features include citation-based RAG for audit-heavy sectors, customizable guardrails and PII controls, intelligent model routing, automated question generation for model testing, and a coding assistant for rapid prototyping. The platform integrates with Google Drive, Slack, SharePoint, GitHub, AWS, and Snowflake, and supports multi-tenant, scalable deployment across cloud and on-premise infrastructure.
H2O.ai's platform is used by some of the most regulated industries globally — financial services, telecommunications, and government — delivering documented outcomes such as a 70% reduction in fraud for a major bank and a 2x ROI on generative AI investment for AT&T.
- Automating fraud detection and KYC onboarding workflows for financial services teams
- Deploying air-gapped enterprise AI assistants for government agencies and federal employees
- Extracting structured data from contracts and compliance documents using Document AI
- Routing customer service inquiries automatically in call center operations at scale
- Fine-tuning open-source LLMs and SLMs on private enterprise data without code
- Generating multi-page PDF reports with charts and tables using autonomous AI agents
- Building domain-specific vertical agents for loan automation and debt collection
- Analyzing audio recordings and visual content with multimodal transcription models
- Managing model risk and compliance with automated evaluation and human feedback calibration
- Integrating predictive AutoML outputs with generative AI for business decision support
