ChainML provides a generative AI-powered API, Council Analytics, that enables natural language interactions with data for software applications, facilitating advanced analytics without requiring complex coding. Their open-source Council framework supports the deployment of production-grade AI agents, ensuring secure and reliable integration across various business use cases.
Funding
$10.2M 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
Many software applications lack the ability to directly interact with data using natural language, requiring users to write complex code or rely on specialized data analysts. This creates a barrier to entry for non-technical users and slows down the process of extracting insights from data.
Solution
ChainML offers Council Analytics, a generative AI-powered API that enables natural language interaction with data for software applications. Council Analytics allows users to perform advanced analytics by simply conversing with their data, eliminating the need for complex coding. The API securely integrates with existing products and data sources, providing a conversational UI for data analytics and mission-critical insights. Council Analytics is built upon the open-source Council framework, designed for the development and deployment of production-grade AI agents.
Target Audience
ChainML's primary customers are software developers and product teams looking to integrate conversational analytics into their applications, as well as enterprises seeking to empower non-technical users with data-driven insights.
Features
- Generative AI-powered API for natural language interaction with data
- Secure integration with existing software products and data sources
- Open-source Council framework for building and deploying AI agents
- Consistent API across different LLM providers, including OpenAI, Anthropic, and Google
- Flexible configuration system for LLM parameters
- Built-in consumption tracking and monitoring capabilities
- Robust error handling and retry mechanisms