Launched this week
Lium AI
AI for Complex Data
195 followers
AI for Complex Data
195 followers
Lium is a collaborative AI platform that helps domain experts get reliable answers from messy, massive, multimodal datasets. Connect terabyte size data in any format, ask questions in plain English, generate knowledge artifacts, and turn verified analysis into reusable workflows your team can build on. Lium brings together data across geospatial, energy, space, and other complex domains so work that once required weeks of engineering can happen in a single conversation.
Lium AI
Hey Product Hunt! Ryan here, one of the co-founders of Lium.
A quick story on how we got here.
A few years ago, my co-founder and I had been working with AI long enough to see both its immense potential and its limitations. The thing we kept coming back to was that much of the world’s most important data is still incredibly hard for AI to work with: too large, too complex, too multimodal, too domain-specific. That’s what led us to build Lium.
Lium is an agentic harness purpose-built for large, complex, multimodal data. It helps teams connect with terabyte-scale datasets, ask critical questions where the answers can’t be hallucinated, generate meaningful knowledge artifacts, and turn ad hoc analysis that used to take weeks or months into repeatable, collaborative workflows in minutes.
We sometimes describe it as: if Cursor and Notion had a baby, it would be named Lium.
We built Lium to be easy enough for anyone to use, including scientists, analysts, operators, domain experts, and data teams working with the messy, massive, high-stakes data that powers the real world.
We’ve poured our hearts into this and would genuinely love your feedback.
Please give Lium a try and let me know what you think!
Nice concept. What's the biggest type of data complexity it handles that traditional BI tools consistently fail at?
Lium AI
Hi @dhiraj_patel5 , great question!
We work with a wide range of complex datasets from advanced industries, including 3D seismic volumes, NDT/inspection data for semiconductor and manufacturing workflows, hyperspectral and remote-sensing imagery, and other large multimodal scientific and engineering datasets.
We also see teams use Lium on large, messy business data, especially in areas like marketing and finance, when the data is spread across files, systems, and formats that are hard to analyze together.
A concrete example: Lium connects to multiple NOAA sources, so you can query terabytes of climate and weather data, often stored in obscure formats, just by asking questions in natural language. To try it, you can sign up for free and turn on the Weather & Climate domain pack, which includes the data connections and a set of pre-built tools.
Hope that helps, and I’d love to hear your feedback if you test it out!
Hey Product Hunt!
Engineer on the Lium team here 👋
The part that doesn't show up in the demo but ate most of our engineering time: making "ask a question in plain English" actually reliable on terabyte-scale, multimodal data. Anyone can wire an LLM to a SQL generator. The hard problems are the unglamorous ones — connecting to formats that were never meant to be queried conversationally (3D seismic volumes, hyperspectral imagery, the NOAA climate formats nobody enjoys parsing), keeping analysis reproducible and reusable instead of one-off, and building guardrails so the model says "I don't know" instead of confidently hallucinating on high-stakes data.
Scaling the processing platform was its own beast. A single natural-language question can fan out into a workload that touches terabytes, so the engine has to parallelize across compute, scale elastically with demand, and handle backpressure gracefully instead of falling over on the heavy queries — all while keeping cost sane so you're not paying for a cluster that sits idle between questions. Getting that to feel instant from the user's side while it's churning underneath was a genuinely hard line to walk.
The design goal we kept coming back to: an analysis you run today should be a reusable, inspectable workflow your teammate can build on tomorrow — not a screenshot in Slack.
@scotthburk it's usually the unglam stuff that really differentiates, right Scott! - great work, man!!
jared.so
Clean launch for Lium Ai: Ai for Complex Data. How are you measuring whether it is working for people?
Lium AI
@borrellbr This is an important one. We have a few ways:
-With early access customers, we had 1:1 calls with all of them to collect feedback first hand. This is where we got conviction that we were really on to something with ~50 teams giving great reviews (and some constructive feedback of course!)
-For a more measured analysis, we have analytics built in to see usage, where people are getting stuck, how many tools they build, how many users they share it with, etc. On average, users are sharing with 2-3 collaborators which is a great sign.
-Soon we will release an evaluation harness that enables the users to track and evaluate performance themselves.
A fun one: an astrophysics researcher using our platform messaged me this morning asking to add me to their paper because Lium has had such a big impact on their work!
@borrellbr appreciate the kind words, Ignacio! 🤟🏽
Hey ya'll, Aron here from LiumAi growth team.... .8 reasons I think Lium should exist: yes I am biased :)
1. Messy, massive, multimodal data shouldn't stand between humanity and its next breakthrough.
2. The answers to some of humanity's hardest problems are trapped inside that data.
3. Data shouldn't require a PhD in SQL to understand.
4. Researchers, engineers, climate scientists, physicists, healthcare teams, and innovators deserve better tools.
5. Humanity reached the moon 🌔 . Enterprise data is still a disaster.
6. Breakthroughs happen when curiosity moves faster than complexity.
7. Some of the world's most valuable discoveries are hiding at the intersection of data that's never been connected.
8. It's fun to support startups trying to do a little good in the world. It's even more fun to watch good people win.
If any of that resonates, we'd love your support today.
Stripo.email
Congrats on the launch! The idea of making large-scale multimodal data accessible through collaborative AI workflows is really compelling.
Lium AI
@alina_tyslenok_ Thank you Alina, appreciate the kind words.