Supernova - All your data in Claude and Codex
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Supernova connects your startup’s live data to Claude and Codex, so anyone can ask questions, investigate performance, and run complex analysis in the AI tools they already use. Connect Stripe, HubSpot, PostgreSQL, and 30+ other apps, then analyze revenue, pipeline, customers, usage, and operations without waiting on engineers or moving everything into a traditional BI stack.
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Hi again everyone!
Luke and Kate from Supernova here.
Great to be back on Product Hunt. We got awesome feedback our last launch so I'm pretty psyched to show off what we've been cooking since then.
Claude and Codex are so good at data now.
The only problem? They don't have all your company data.
With Supernova now they do!
How it works:
Connect your apps to Supernova.
Connect Supernova to Claude or Codex
Let the models create beautiful dashboards and powerful models.
Why Supernova?
Batteries included - no extra data warehouse or ETL needed
Modern features: Iceberg exports, MCP, git
Transparent pricing for startup budgets
Swiss army knife CLI included
Truly open source
It just works
We'd love for you try out Supernova. We're offering 20% off Supernova for 6 months (and we're already crazy affordable compared to alternatives).
Let us know what you think! We love feedback - our best ideas come from users ❤️.
Get started at supernova.ai!
@lukezapart Nice launch congrats 🙌bypassing raw CSV exports and letting Codex interact with real app data natively is brilliant. qq how are you guys managing real-time data syncs across app integrations without hitting rate limits?
@priya_kushwaha1 Thanks! It's been really fun gearing up for launch. Each data source has different limits, so we had to build some machinery to adapt to a given platform's rate limits. We aim to be nice!
We sync that data into a super fast data lake we built which has no such rate limits, so after you sync to Supernova you can quickly run queries on millions of rows.
@lukezapart That makes sense the different rate limits can definitely be tricky like a smart way to handle it. all the best for launch🙌
Is this expensive? At a previous company we paid a lot for a fortune for data warehousing and syncing
@chris_nguyen3 Nope! We often cut data costs by 80-90% for customers who switch from other data platforms to Supernova. And as a bonus if you connect directly to the MCP you get to use your existing Claude subscription instead of paying us for tokens.
Well designed;
How does this compare to leveraging OpenAI/Claude provided dashboard that can connect to all of your data sources already and present them as desired?
I'm not understanding why a tool needs to sit in the middle; feels like more of a vitamin than a pain killer tool.
@chrisgibsontech Thank you!
Data governance is a big one - you can set table permissions per person and even for the person's MCP. So Alice in Accounting can access finance tables via Claude but Bob in Marketing cannot (but can still access ad performance numbers).
Another is rate limits and performance at scale. If you have a million records in an app, syncing them takes hours/days. So if you wanted to calculate the median order value for example, you couldn't really do that with just Claude. But with Supernova, the data syncs in the background; Claude runs a query and you get a result in a second.
Supernova also has built-in git version history for dashboards and durable models so you can work on the same data projects with many people.
I’m intrigued by how @Supernova auto‑formats posts to match each platform’s best‑practice guidelines. How do you balance platform‑specific recommendations with a unified “best‑fit” option when the same content performs differently across channels? In building our own tool, we found that letting users choose a single optimized format reduces friction, but we also keep a “platform‑specific” mode for power users who want to fine‑tune.
Congrats on the launch! Keeping the analysis inside Claude/Codex instead of adding another BI interface feels like the right direction. Can a team define metrics like MRR or “active customer” once, so everyone gets consistent answers across different prompts and agents?
Connecting live company data straight into Claude and Codex without traditional ETL setup is brilliant. Huge congrats on the launch!
@thisiskp_ Thanks KP, much appreciated :)
Love that Supernova meets teams inside Claude and Codex instead of forcing everyone into yet another BI dashboard, that alone removes so much friction from getting answers.
@ilko_kacharov Thanks Ilko! Yeah, we all practically live in Claude and/or Codex these days, so it feels like the natural next step.
Good to see you back for a second launch. Table permissions went from private preview to shipped for everyone while the thread was still running. Congrats on that turnaround.
@lucasjpols Great to be back. PH is so great for product feedback.
the thing i would want to know most: when someone asks what revenue looked like last month and the model has the right rows in front of it, how often does the number come back right?
we pointed eight models at a live pricing api recently and two of them misread a quantity ladder they had been handed correctly. not hallucination, the data was in context, they just read the wrong row. one was out by 4x, the other by about 6 percent, and the 6 percent one is the dangerous one because nobody double checks a number that looks plausible.
for a support reply that is an annoyed customer. for revenue analysis it is a number that ends up in a board deck. do you verify the arithmetic anywhere before it renders, or is that left to the model?
@jernej_jan_kocica for important numbers (such as ones that end up on a deck), I run adversarial review agents, just like code. E.g. give something like this to Fable:
"This is a revenue analysis we don't fully trust. Do an adversarial review of the numbers, methodology and data sources used. These numbers will be used on a board deck so it is critical that we avoid mistakes."
Or maybe "Spawn multiple agents to cover distinct ways in which the numbers could be wrong"
In our own harness in-app we built this Orchestrator -> Implementer -> Reviewer workflow for that reason. For Claude unfortunately the MCP rules don't allow us to instruct the model on its behavior too strongly, but you can implement a similar workflow yourself.
We should probably publish some docs on this!
Of course, for something like an actual board deck I would still probably review manually myself.
@lukezapart that is more concrete than i expected, thanks. the orchestrator to implementer to reviewer split is the part i want to steal.
the bit i am still unsure about is whether an adversarial pass catches the quiet error. a reviewer asked to find problems with 39.00 finds it, because it is wrong on its face. a reviewer looking at 9.00 against the same price ladder has to read that ladder correctly in order to disagree, and something just misread it once already. plausible errors survive review for the same reason with people and with models.
your last line is the honest one though, and it is where we landed too. for anything that actually matters a person still reads it before it goes out. this is the third time this week someone has independently told me the answer is a separate verification pass, which is starting to make me think that is the state of the art rather than a workaround.
would genuinely read those docs if you write them.