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.
Hi Product Hunt - We’re Hoshang & Vishal from Airbook - An AI native workspace to do all your analytics work in one place.
Airbook automatically syncs, cleans and centralizes all your data scattered across HubSpot, Amplitude, GA4, Zendesk, Stripe, Postgres, Snowflake and more - You can then use Airbook AI to build powerful interactive reports and unified dashboards.
Our AI is schema-aware -It understands your fields, relationships, and can auto-build queries across sources with context. You can join sources like HubSpot + Salesforce + Snowflake for example. Every query it generates is editable, so you always stay in control. From there, you can prompt it build a dashboard for you or trigger workflows to push data into Customer IO, Clay, and more.
We built Airbook after years of leading data and ops at high-growth startups, where every question → insight → action flow involved bouncing between ETL scrips, CSV exports, warehouse queries, SQL Notebooks, BI tools, docs, decks and more. GTM, Ops, and Data teams were chasing the same answers, but each lived in totally different tools. We’ve now seen dev workflows evolve fast - Cursor, Claude, Copilot - but analytics still feels like it’s stuck.
Airbook is the common meeting point: one place to explore, present, and activate data, using interfaces you already know how to use - SQL, point‑and‑click, and now AI.
Three ways to work:
1. SQL IDE for technical folks
2. No-code builder for business users
3. AI assistant for both
Analytics and Ops teams use Airbook for deep dives, data exploration, quick answers, and cross-functional reporting. And because it’s collaborative, business teams can self-serve insights using the no-code builder too.
Teams also use Airbook to build segments by joining data from tools like Postgres, Amplitude, HubSpot and then trigger a workflow to push these segments to growth tools (Customer IO, Clay etc.) and launch campaigns instantly.
Here are some examples of what you can ask our AI:
🔺 Help me build a full funnel report from Traffic (GA4) → Leads (HubSpot) → Opportunities (SFDC) → Revenue (Stripe) with monthly conversion rates | *Funnel Reporting*
🔺 Traffic spiked in December, help me identify which sources caused this and whether it led to increased leads and opportunities | *Exploration*
🔺 Build a segment of enterprise trial signups who created at least 1 project, requested pricing info, and remain in the 'Qualification' stage in HubSpot | *Segmentation*
🔺 Create customer health scores by combining revenue, support interactions and product usage to identify potential churn risks | *Scoring Models*
We just launched a freemium plan - connect to a database and start using Air AI. You also get a 14-day free trial with full access. And with our MCP, you can build on Airbook or fetch insights straight from your favorite AI tool.
Your feedback shapes our roadmap so over to you now - what’s the first report or workflow you’d build with Air AI, how smooth (or bumpy) was the setup, and what could we do better? Share your honest thoughts - friction points, dream features, must‑have integrations - in the comments. We're super excited to hear from you!
Happy Building!
Team Airbook
This is awesome!! I have been a career data analyst and am looking forward to checking it out once I have my startup up and running in a month
congrats guys! it's been a while that I wasn't impressed by a cool analytics products, but you did that! Sounds like you are very feature packed, and love that fact you can sync back cohorts to marketing platforms. SMASHSEND integration :p
This is shockingly well made. Feels like the Supabase AI assistant; but with every source + visualizations. Love it. Great job!
Awesome launch, Airbook! Sync-clean-analyze-activate all in one—impressive!!
Airbook AI is a powerful tool for business analytics, but data privacy remains a major concern. Many companies are reluctant to share sensitive data with external platforms, which limits adoption.
One solution is for businesses to build internal AI-driven tools for secure data analysis. While Airbook AI is highly functional, its best fit may be in local or small-scale environments where data governance is more flexible
Airbook AI turns data chaos into clarity. It connects to your CRM, support, and product tools understands your schema, writes SQL, joins sources, builds dashboards, and even triggers workflows. All in one place, just ask.
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?
@hoshang_m Congratulations. And happy product launch.
@hoshang_m@vishalbajaj@priyansh99 Big congrats on the launch! On the implementation front - how technical would one need to be to roll this out?
Sounds really powerful! I like how it brings everything together in one place and makes it easy to act on. Curious to see how it handles more complex joins and big datasets in real use
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! 🔥
ou probably know Cursor tends to hallucinate a bit. For example, if you ask it to just change a component’s color, it might rewrite unrelated parts entirely. How does Airbook handle those moments?
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?
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!
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 :)
