This looks awesome! I wish I could connect to my Postgres DB using SSL.
As an update, we now have SSL connections available
Readit NewsClaireGz commented on Launch HN: Nao Labs (YC X25) – Cursor for Data · Posted by u/ClaireGz
Hi, this is a great idea. I'm trying to get it working but I'm having some trouble in the last step of "Configure dbt project". I'm looking for a support link on your website but can't find any.
Here is our contact page, feel free to contact us and we'll hep you setup: https://docs.getnao.io/docs/support/support
Also, we'll be adding a new dbt onboarding flow tomorrow!
I can't really tell what those databases are that are coming soon, a "hover" over the icons would be nice. SQLServer coming anytime soon, my coworkers are working on some data integrity work right now and it might be a nice tool for them.
It's Databricks, Iceberg and Redshift, which on the first survey that we did were the most asked. But as per this post and a broader audience it appears SQLite at least win! We'll add also SQLServer in the list
Any plans to add support for ClickHouse? If so, what does that timeline look like?
Probably in a few months. For now we're focusing to make the experience great for a restricted number of warehouses. But you can reach out by email and we'll keep you updated
This looks like many LLM assisted data projects which help and are flexible, but aren't repeatable and aren't fast enough to be interactive. Nao is a good execution of the concept.
I built Buckaroo as a data table UI for Jupyter and Pandas/Polars, that first lets you look at the data in a modern performant table with histograms, formatting, and summary stats.
Yesterday I released autocleaning for Buckaroo. This looks at data and heuristically chooses cleaning methods with definite code. This is fast (less than 500ms). Multiple cleaning strategies can be cycled through and you can choose the best approach for your data. For the simple problems we shoudn't need to consult an LLM to do the obvious things.
All of this is open source and extensible.
[1] https://youtube.com/shorts/4Jz-Wgf3YDc
[2] https://github.com/paddymul/buckaroo
[3] https://marimo.io/p/@paddy-mullen/buckaroo-auto-cleaning Live WASM notebook that you can play with - no downloads or installs required
Thanks for sharing. I like the view you built to visualize the profiling of your data, I think that's indeed key to understand your data.
How much data is hitting your models/prompts? I am okay with you knowing about my schema, but a lot of warehouse data is sensitive data. I saw you have enterprise plans, and maybe that is my answer, but I’d love to know ahead of time if data/results are hitting your servers in addition to the code, or if it’s code-only.
The content of the data is never going to the models, unless you specifically grant access. Our server only store embeddings of your codebase and data schema.
The content of the data is only accessed locally by your computer. When you ask our agent to run a query for you, it will execute it on your warehouse, then ask you for permission to read the result. If you don't allow it, you'll be able to preview it locally without sending it to the LLM.
The enterprise version is for your if you want to be sure the prompts and context you send to nao don't go through a public LLM endpoint and get trained on.
Been using this for several weeks now and it's genuinely improved my workflow—I'm choosing it over VSCode and extensions more than half the time.
The chat for exploratory data analysis ("what can you tell me about this column I just added?"), the worksheets and column lineage are real game-changers for dbt development. These features feel purposefully designed for how I actually work.
Claire and Christophe are super responsive to feedback, implementing features and fixes quickly. You can see the product evolving in all the right directions!
Thanks for your kind message — and for helping us make nao better!