Anania - Search your data and find insights under 5 seconds
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Anania is a Robot data analyst. You can ask questions about your data in plain English, and get answers instantly! Anania has a Generative AI system which turns your questions into SQL queries and Python code, executes them on your data.
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Nice idea, very intrigued to try this out in real time! This has HUGE potential!
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Do you have an integrations roadmap available?
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Congrats on the launch guys, this is an exciting space to bring together a messy world of applications!
@dan_robins hey Dan, we are currently providing file upload and relational DB connection. Next up are CRMs (SalesForce and HubSpot), Data Warehouses (Snowflake and RedShift) and then we are thinking about either Shopify or AirTable.
@dan_robins anything specific that you would like to see?
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@hrantdavtyan Sounds like a great roadmap! I was wondering whether you might also look to integrate with some tools like Miro and Mural (seems to be where a lot of teams are storing data and collaborating - but notoriously difficult to search through!)
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Hey, this is quite interesting, I wonder whether I can share my searches or results with other team members?
@artem_harutyunyan Hi, thanks for the question. Currently we support CSV/Excel file upload and PostgreSQL DB connection. Other sources are available per request.
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Congratulations! Great tool for data analysis, I liked the SQL part.
@b2bb2c Great idea. What you would like to see in our app specifically for fintech?
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Hey, congrats for the launch! I was wondering, is the generated SQL efficient enough to work (in reasonable time) on very big databases ? My fear is, if you are using generative model, you might have a problem where the SQL generated works in theory but won't in practice due to size of the DB. Or is it already efficient enough? Do you use the size information in the prompt to the generative model? What are your results on this matter?
Thanks!
@gregoire_ret that's a key question thanks, especially from our Enterprise users!
at this point, we optimized the model to generate as optimal SQL as possible, but we will never have full control. we are planning to integrate a 3rd party tool, which measures the efficiency of SQL before execution and automatically makes improvements. that is on the Q1, 2023 roadmap
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@hrantdavtyan Amazing! Yeah I feel like a post-processing approach by another tool is the most reasonable solution as "you can never be sure with DL". Thanks for answering :)
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