Inconvo provides an API that makes it easy to embed a data analysis assistant directly into your app.

We noticed how emerging analytics assistants like Posthog’s Max AI, Amplitude’s Ask, and Mixpanel’s Spark AI significantly streamline data interactions, enabling both technical users to be more productive and non-technical users to interact directly with the data they need.

These tools are powerful, but building something similar from scratch is complex, especially handling multi-tenant databases, contextual awareness and building a text-to-SQL agent. Developers often find themselves buried in LLM complexities which takes time away from core product development.

We encountered this pain ourselves while trying to build conversational analytics for another project. Recognizing how challenging and common this build was, we decided to build Inconvo specifically to simplify this process for developers.

Inconvo provides an end-to-end analytics assistant accessible through a single API call. Our API returns structured JSON responses consistently across text, chart, and table outputs, and our platform abstracts away complexities including semantic modelling, multi-tenant filtering, and AI model evaluation and monitoring.

To illustrate, we've integrated Inconvo with an e-commerce demo app here: https://demo.inconvo.ai. The assistant interacts directly with the app’s database (fully inspectable here: https://demodata.inconvo.ai). Feel free to try it, break it, and give us feedback!

Our developer docs are here: https://inconvo.ai/docs and we also created a straightforward React-Node integration example: https://github.com/ten-dev/inconvo-react-node-example

We’re grateful for the chance to share this, thanks for reading! We’d really value your feedback or questions below.