Chata.ai provides a natural language processing platform that enables businesses to access and analyze data through custom language models, allowing non-technical users to generate insights and set alerts in real-time. By reducing operational costs by 99.8% with CPU-based inference, the solution enhances data accessibility while maintaining full control over data security within the user's environment.
Funding
$11M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Business users often struggle to access and analyze data efficiently, requiring them to rely on data analysts or IT support, which can be time-consuming and costly. Traditional business intelligence (BI) tools often lack the ease of use and accessibility needed for non-technical users to independently derive insights from their data.
Solution
Chata.ai provides an API-first, natural language querying platform called AutoQL that enables business users to access and analyze data through natural language. AutoQL uses proprietary technology to create custom language models tailored to an organization's specific databases, allowing users to ask questions, filter data, and set up custom data alerts in seconds. The platform offers flexible widgets like Data Messenger and Dashboards that can be embedded into existing software or portals, providing self-service data access and enhanced reporting capabilities within the user's existing workflows. By using CPU-based inference, Chata.ai reduces operational costs compared to large language models (LLMs) while maintaining data security by deploying custom language models within the user's environment, whether in their cloud or on-premises.
Target Audience
Chata.ai targets business users, data analysts, and IT teams within organizations of all sizes who need to provide easy, secure, and cost-effective data access and analysis capabilities.
Features
- Natural language interface for querying databases, enabling non-technical users to access data insights
- Custom language models tailored to specific organizational databases, ensuring accurate and relevant results
- API-first architecture for seamless integration into existing software, portals, and applications
- Data Messenger and Dashboard widgets for embedding self-service analytics capabilities
- Proactive data alerts that notify users of key changes and trends in their data
- CPU-based inference for cost-effective and scalable performance
- Secure deployment options, including cloud and on-premises, ensuring data remains under the user's control
- Mobile accessibility, allowing users to access data on demand from anywhere
- Integration with Microsoft Teams and Excel