Product Thumbnail

Lume

Automate data mappings using AI

Developer Tools
Artificial Intelligence
Data & Analytics

Use AI to automatically map data between any two schemas in seconds. Lume AI helps teams ingest client data, normalize data from different sources, and build data pipelines, automatically.

Top comment

Hi Product Hunt 👋  @nebyou_zewde1 , @robert_te_ross , and I are the founders of Lume. 🧨 Problem: Data Mapping is manual and slow We are on a mission to automate the painstakingly manual process of data mapping, after experiencing this frustration as engineers ourselves. The usual mapping process involves a labor-intensive cycle: analyzing data to determine what's relevant, selecting the appropriate properties, developing the mapping logic, and constantly updating mappers to accommodate schema changes in source or target systems. This process, we learned, takes days, weeks, or even months for most teams, and automating it has traditionally been borderline impossible due to unique differences in data. 🚀 Key Features - ✨ Generate mapping logic in seconds: via our API, just pass in a sample of your source data and a target schema, and Lume will generate a mapper. - 🛠️ Edit mapping logic: review and update the mapper as needed to ensure you have the desired outcome. Leverage natural language to edit the mappers quickly and easily. - ✅ Deploy mappers: once you’ve reviewed the mapping logic, save the mappers to use them deterministically in your code via our API, allowing you to reliably move data between schemas as you scale your data pipelines. - 🤖 Auto-maintain mappers: Lume detects changes in your schemas, notifying you and allowing you to use AI to update the mapping logic, effectively automating your maintenance. - 📊 Manage and organize mappers: use Lume’s dashboard to have visibility over all of your mappers and live data pipelines. - 🔮 Upcoming: viewing the generated mapping logic, and adding custom logic. 💡 Use Cases Lume handles three core use cases: - Normalizing Data from Various Providers - Client Data Ingestion - Rapid Setup and Maintenance of Data Pipelines All of these have the common theme of having to map data between unique schemas, where even discrepancies as minor as column name variations make this process time-consuming and near-impossible to automate. This gets even worse at scale. 🎯 Who’s this for? We are actively talking to small to midsize startups that are bottlenecked by data mapping on any of the above 3 fronts, but are also excited to serve larger companies and use cases beyond. 👀 Try Lume Request a demo via https://www.lume.ai. We offer a free pilot. I’ll reach out to you promptly and get you onboarded quickly. 📖 Our story As engineers ourselves, we’ve spent plenty of time grudgingly going over the manual task of mapping data. We quickly learned that we were not the only ones who faced this problem - most companies spend too much time on this. As AI grads from Stanford, and with a fire for this problem, we built Lume AI. We are part of the Y Combinator W23 batch, and we’re excited to be launching here. 💰 Special Pricing Email me mentioning you saw Lume via Product Hunt, and we will give you a 50% discount for your first 6 months! We also offer a free pilot.

Comment highlights

I work with Bubble a lot and one of the challenges I've seen people having is managing schemas especially when they've started from a reference, tutorial or a template. Lume seems to completely eliminate that problem. I'll be spending the weekend experimenting with it! Love what you're doing @nebyou_zewde1 , @robert_te_ross, @nicolas_machado :)
congratulations with the launch. Looks great. Guys, how much time did it take to develop the product? From the idea to the current result?
as someone building an ai product, this makes SO MUCH SENSE. looking forward to seeing lume evolve into supporting unstructured data.