Livedocs

The general data agent

Analytics

Artificial Intelligence

Business Intelligence

Love that you didn't dumb it down too much—keeping the full notebook mode with SQL/Python is a smart move for power users. 🐍 regarding the environment: Can I import standard Python libraries (like Scikit-learn or Prophet) for forecasting, or is the sandbox restricted to basic Pandas operations?

Congratulations on your launch. Is there any limitation on the number of data points you currently allow in one file?

Very interesting! How do you achieve search accuracy in your database? Even models like ChatGPT 4.x often don’t search databases very precisely. Do you use special models, handle it at the prompt level, or do something else to ensure accurate search? I have a similar task: a large travel database, and I need to extract the right information based on queries. Could you give a couple of tips on the best way to do this?

Can it do what Python does?

What's the line limit for LiveDocs?

Besides data analysis, what does it serve?

Congratulations on the launch. Livedoc looks like promising tool for modern data analytics respect speed and comprehensiveness. I like that

Congrats on the launch @arslnb 🎉 Do you have any affiliate/partner program?

This looks refreshingly simple. Upload data and ask questions in plain English—no dashboards or SQL is a big win. Curious how it handles messy real-world CSVs. Great concept 👍

@arslnb congratz on the #1! How do you guys differentiate from other lightweight AI analyst tools, like Airbook, Wobby, Zenlytic, Wren AI, etc?

Btw, as a launch fellow, adding you to our directory of AI analytics tools right away:)

Has been great so far. I love being able to collaborate on a notebook with my colleagues to build meaningful reports for our clients. Never thought that doing the analysis part with “messy” data would be so seamless.

Our work takes us to remote locations in Australia with limited internet connectivity. How easy is it to set up offline?

LiveDocs 5 is a solid all-in-one workspace for data analysis and collaboration. I like how it combines AI-powered insights with SQL, Python, and visualizations in one place, making it easy to explore data without constant tool switching. There’s a small learning curve at first, but once you get used to it, it feels powerful and flexible for real data work.

This looks super useful for quick insights. What’s the stance on data privacy? Is the uploaded data used to train your models, or does it remain completely isolated within the session?

From my experience, the biggest bottleneck with data tools isn’t lack of power — it’s the friction between questions and answers. Most teams don’t want to build dashboards or write SQL just to explore an idea.

I like how LiveDocs keeps the workflow conversational but still allows you to go deeper with notebooks when needed. That flexibility is important — especially for founders and ops teams who want quick clarity first, then depth.

Curious how teams handle versioning or sharing insights across stakeholders once analyses evolve. Overall, this feels very thoughtfully designed. Nice work 👏

The plain English querying is interesting - does it handle complex aggregations well, or is there a learning curve for getting the right phrasing?

How to handle data in a cluttered environment? What are the high requirements for data quality?

Congrats on the launch! this is really cool!

I'm a Senior Data Scientist in Fintech (lending/capital markets), I’ve spent some time building scrappy agentic workflows with aws to answer executive questions like 'What was the loan churn rate trending MoM before the Oct spike?' The friction usually comes from the 'agent' losing context on our specific schema or failing at complex temporal joins.

The Livedocs UI looks incredibly clean, and the 'Notebook + Agent' hybrid approach I can definitely see myself using

From a Fintech perspective, I have two questions:

1. Privacy & Infrastructure: Since we deal with sensitive credit data, what’s the 'Enterprise' story? Can this be self-hosted or deployed within a VPC (AWS/Azure) to bypass the legal hurdles of third-party data hosting?

2. The Databricks Differentiator: We currently use Databricks with Copilot for SQL/Dashboards. How does Livedocs handle the 'governance' layer differently? Is it meant to sit on top of our existing Unity Catalog, or is it a complete alternative for the presentation layer?

I’d love to stress-test this with some of our non-PII datasets. If you're looking for more technical feedback or a user interview with a DS in the lending space, feel free to reach out at [email protected]

Upvoted and watching closely!"

The ability to run locally with your own GPU is a nice option for sensitive data. I'm curious about the schema inference—when connecting multiple data sources with overlapping but slightly different schemas, how does Livedocs handle reconciliation? Does it prompt for manual mapping or attempt automatic resolution?

"No SQL, no dashboards, no setup" is the right democratization approach. The real barrier to data insights isn't tools – it's the translation layer between business questions and technical queries.

Interested in how you handle data quality edge cases. When users ask ambiguous questions ("show me growth"), does the agent surface assumptions or clarify intent before generating charts? That context awareness would be key for trust in production.