HipAI automatically builds context graphs from both structured and unstructured data, enabling a unified view of a business without the need for data copying or ETL processes. Its agents leverage these graphs to answer complex, real‑world questions up to 50% more accurately, and the system continuously updates the graph with new knowledge, requiring zero maintenance.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations often struggle to integrate structured databases and unstructured documents into a unified knowledge base, requiring time‑consuming ETL pipelines and data duplication. This fragmentation hampers AI agents from accessing the full context needed to answer complex business queries accurately.
Solution
HipAI automatically generates context graphs that connect data from relational databases, document repositories, and chat logs without copying or ETL. The platform continuously updates the graph as new information becomes available, maintaining a single source of truth. AI agents built on this shared context can retrieve the right data for each query, delivering answers that are up to 50% more accurate. By providing a unified context layer, HipAI improves AI query performance by 30–70% compared with competing solutions. The system operates with zero manual maintenance, allowing businesses to deploy smarter agents in minutes.
Target Audience
HipAI is aimed at enterprises and data‑driven teams that need to power AI assistants, analytics platforms, or decision‑support tools with a comprehensive, up‑to‑date knowledge base spanning databases and documents.
Features
- Automatic construction of context graphs from both structured (SQL, Snowflake, etc.) and unstructured (documents, chat) sources in minutes
- Real‑time graph enrichment where agents add newly discovered knowledge, eliminating the need for manual ETL updates
- Shared knowledge representation that can be accessed by any downstream AI agent or application
- Performance boost of 30–70% for AI question answering, with over 50% higher accuracy on complex queries
- Multi‑modal data integration enabling unified view across databases, files, and conversational data
- Scalable cloud architecture that supports large enterprise data volumes without data duplication