alexliu518

Thank you for your support

Thank you very much for your support. If you have any questions, please feel free to give us feedback.

Two main aspects: 1. How to handle the data related to the target problem; 2. Choosing suitable charts to present this data. #1. By leveraging the increasingly powerful coding capabilities of LLMs, we can appropriately process raw data to obtain a dataset that closely aligns with our goals; #2. We expanded echart and utilized its rich chart types already supported, along with the Univer SDK from the Univer team, ultimately creating tables.

Very critical question. Excel is indeed more complex. Before analysis, Capalyze first preprocesses the data, which is crucial. We have designed a set of preprocessing algorithms that essentially focus on how to better identify the data suitable for analysis in Excel and clean and repair it. This process also leverages LLMs, as we found that LLMs perform quite well in recognizing table structures.

Hey HN,

I’m one of the developers behind https://capalyze.ai, an AI-powered tool that helps small teams analyze their data using natural language — no code, no templates.

The idea came from conversations with indie e-commerce sellers and creators who had _tons_ of data (spreadsheets, reviews, exports from marketplaces) but lacked the time or tooling to make sense of it.

With Capalyze, you can:

1. Ask questions like _"What are the most common complaints in these reviews?"

2. Paste or upload product data and get a summary of pricing trends

3. Generate charts, compare columns, or extract keywords — just by asking

It works best with your own datasets right now (CSV, Excel, etc.). Web scraping isn’t live yet— we’re actively building it, and you can follow our updates if that’s important to you.

We’ve tested it with early users in e-commerce, real estate, and content — and the feedback has been super helpful. One user called it “ChatGPT with a purpose.”

We’d really appreciate feedback from the HN community:

1. Is the interface intuitive?

2. Are the responses helpful and explainable?

3. What would make this more useful for you?

Here’s the link: https://capalyze.ai Happy to answer questions and chat more about how we built it (multi-model backend with OpenAI, Claude, DeepSeek, plus a simple orchestration layer).

Thanks!

Very good application, but it seems that the video cannot be played after uploading

Very useful project, keep it up

Very interesting project, how to copy and save ascii characters

I understand your idea, but if you are sure that a software is excellent, then paying for it is a good habit.

Converting web pages to Markdown is a common requirement. I have found that turndown does a good job, but it cannot meet the needs of all dynamic web page content. As far as I know, if you need to process dynamic web pages, you need targeted adaptation, such as Google extensions such as Web2Markdown.

Very comfortable and simple UI

Interesting

Great work! Keep it up!

I think it is a very worthwhile project, thank you for your work

Cool! Keep it up!

ok

Cool

Thanks for sharing TargetJ! It’s intriguing how it can animate anything. Could you share how it simplifies animation creation and its performance in handling complex scenes?

This looks fantastic! What AI models do you use?

This is awesome! Quick questions:

How do you handle the massive data scale and keep it all up-to-date? Have you faced any ethical challenges with scraping so much public data?

Thank you for the clarification! It's great to hear more about the efficient data management practices at Notion. Your team's innovative use of the data lake to streamline the reindexing process while ensuring user data privacy is impressive. Keep up the excellent work!

Interesting, keep it up!

cool

This looks fantastic! Excited to try Dropbase for building quick, customizable web apps with ease.

Thank you for your advice and guidance. I have learned a lot.

Very direct and efficient processing method

Thank you for your recommendation

Flutter is indeed a very good development framework. I heard that many people use it to develop mobile apps. I will try it on the desktop.

Your descriptions are very inspiring to me, thank you. I am a front-end development engineer with 4 years of experience and I don't know much about desktop development. I have heard of Electron, but I understand that its package size and performance are difficult to control, so I am looking for other solutions and best practices, and want to try more possibilities.

I strongly support your idea, although few people do this now. This is the spirit that contemporary programmers lack.