Airbook AI - Cursor for Analytics
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Airbook AI connects to your CRMs, marketing, support, and product databases - understands your schema, auto-writes SQL, joins across sources, creates charts, builds dashboards, and activates workflows - In one place, on command.
Replies
Sellinger AI
Hey,
Congrats on the launch! Just supported. We launched today too if you’ve got a minute to peek.
Pylar
@etien_bresciani Thank you! Already supported :) Looks quite interesting!
Hey, this looks great!! I will gladly supprt. We just launched today too!
Pylar
@ryan_o_neill3 Thank you for your support and best of luck for your launch! Checking it out now.
Enigma X - Personal Encryption Machine
Congrats on the launch@hoshang_m ! Following your journey from the first launch. Funny thing - that's a second time we're launching on the same day :)
Pylar
@jack_khrapkov Hah what a coincidence :) Checked out your launch, looks super interesting! Best of luck and thanks for checking us out here!
350+ E-Commerce Tools Database
Looks great! How did you guys handle having the AI do math? I've found that it's frequently incorrect, especially with large datasets. Speaking of large datasets, how much data can it handle?
Does the platform make inferred connections between different data sources and how? In other words, let's say I have a Shopify site's analytics and Google Analytics connected - where would it pull traffic or conversion numbers from? Having worked with some BI platforms in the past, these were all manual decisions and could be extremely tedious.
Last question - do you get to review whatever data it pulled to analyze do you can manually check against the output?
Great job! Congrats on the launch!
Pylar
@anthony_latona Thanks! 🙌 On the math side - Airbook doesn’t ‘approximate’ the AI writes SQL with full understanding of your data schema, fields, and relationships, so calculations stay accurate even with millions of rows. Essentially it can handle easy to complex calculations via SQL. And yes, our architecture is built to handle millions of rows.
For joining data across sources (like Shopify + GA), since the AI looks at your schema, It can infer the best way to connect them, but if there’s ambiguity - for example, deciding whether to pull traffic from Shopify or GA - it’ll ask you to choose from the tables it thinks your data is possibly in. That way, you’re in control, not guessing. Having said that, the more detailed your prompt is, the better- like in the case of all major AI tools.
And yes, every query the AI generates is fully visible and editable. You can see both - the SQL and the output so you can always see where the data came from, if something's off or you want to quickly add in a field/logic you can tweak the query via the IDE or ask AI to do it, and rerun the analysis before finalizing the output.
Does this help?
350+ E-Commerce Tools Database
@hoshang_m That's awesome, very well thought out and well explained. I wish I had big datasets to try it out! I'll keep it in mind for the future for sure.
Pylar
@anthony_latona Absolutely! Happy to help anytime!
Voquill
Looks solid, makes analytics feel a lot less messy. Congrats!
Pylar
@henry_habib Thank you! Looking forward to having you try us out!
Trufflow
Excited to be launching on the same day as Airbook! I love that the team has also built a way to use Airbook for non-technical users. Curious on what Airbook's future roadmap is for Finance analytics outside of the GTM space?
Pylar
Congrats on your launch 🎉🎉
Amazing tool ❤
Pylar
Massive congratulations on launching Airbook AI! This is exactly what the analytics space needed—bridging that gap between technical and business teams has been a pain point forever. Love how you've made data exploration conversational while keeping SQL control for the technical folks. Quick questions: (1) how does the schema-aware AI handle complex many-to-many relationships when auto-joining sources, and (2) any plans for real-time streaming data integration beyond the current batch connectors? This feels like a game-changer for cross-functional data collaboration! 🔥
Pylar
@replibee Thank you! For complex many-to-many joins, the schema-aware AI understands your fields, keys, and relationships across sources before writing any SQL. It’ll pick the right join paths based on context, and if there’s ambiguity, it asks you to confirm rather than guessing.
On real-time data - right now, our connectors are batch-based, but streaming support is on the roadmap. The goal is to let you run the same conversational analysis on live data without changing your workflow, so you can go from insight to action instantly..
HarnessRouter
@hoshang_m Congratulations. And happy product launch.
Pylar
@huisong_li Thank you!
Airbook AI's seamless integration across all my data sources is a game-changer for my workflow! But what exciting new integrations are you planning to add next to further revolutionize data analysis?
Pylar