Back to Home11/19/2025, 5:02:53 PM

Show HN: We built an AI tool for working with massive LLM chat log datasets

platypii
11 points
1 comments
There’s an important problem with AI that nobody’s talking about. AI’s entire lifecycle is tons of data in for training, and an even larger amount of text data out. Traditional tools can’t handle the sheer volume of text, leaving teams overwhelmed and unable to make their data work for them.

Today we’re launching Hyperparam, a browser-native app for exploring and transforming multi-gigabyte datasets in real time. It combines a fast UI that can stream huge unstructured datasets with an army of AI agents that can score, label, filter, and categorize them. Now you can actually make sense of AI-scale data instead of drowning in it.

Example: Using the chat, ask Hyperparam’s AI agent to score every conversation in a 100K-row dataset for sycophancy, filter out the worst responses, adjust prompts, regenerate, and export your dataset V2. It all runs in one browser tab with no waiting and no lag.

It’s free while it’s in beta if you want to try it on your own data.

Discussion Activity

Light discussion

First comment

6m

Peak period

1

Hour 1

Avg / period

1

Comment distribution1 data points

Based on 1 loaded comments

Key moments

  1. 01Story posted

    11/19/2025, 5:02:53 PM

    2h ago

    Step 01
  2. 02First comment

    11/19/2025, 5:09:13 PM

    6m after posting

    Step 02
  3. 03Peak activity

    1 comments in Hour 1

    Hottest window of the conversation

    Step 03
  4. 04Latest activity

    11/19/2025, 5:09:13 PM

    2h ago

    Step 04

Generating AI Summary...

Analyzing up to 500 comments to identify key contributors and discussion patterns

Discussion (1 comments)
Showing 1 comments
platypii
2h ago
I started Hyperparam one year ago because I knew that the world of data was changing, and existing tools like Python and Jupyter Notebooks were not built for the scale of LLM data. The weights of LLMs may be tensors, but the input and output of LLMs are massive piles of text.

No human has the patience to sift through all that text, so we need better tools to help us understand and analyze it. That's why I built Hyperparam to be the first tool specifically designed for working with LLM data at scale. No one else seemed to be solving this problem.

View full discussion on Hacker News
ID: 45981930Type: storyLast synced: 11/19/2025, 6:23:53 PM

Want the full context?

Jump to the original sources

Read the primary article or dive into the live Hacker News thread when you're ready.

Read ArticleView on HN