Netter
AI native Palantir for mid market.
About Netter
Netter (YC P26) helps companies regain control over their data, so teams can pilot their activities with high precision. Most companies are sitting on years of valuable data, spread across different formats and disconnected tools that don't talk to each other. Netter brings technical capacity to companies that don't have an army of data engineers, and tackles their most complex data challenges. - A nursing home group was chasing unpaid invoices manually across disconnected tools. Netter centralized the collection workflows, automated reminders, real-time visibility, task routing. - A retail chain had years of loyalty card data sitting unused. Netter cross-referenced it with public demographic data to build precise customer segments and trigger the right promotions to the right people.
Public traction evidence
Each signal links to the public source used for attribution.
- LinkedIn
Very happy to share that we got into the YC spring batch.
Very happy to share that we got into the YC spring batch. The founder explicitly says he is building Netter (YC P26). The post says Netter's frontier models are already in production. Visible metrics: 635 likes, 635 reactions, 141 comments.
- LinkedIn
From the cover of Nature to the agents of Netter (YC P26).
From the cover of Nature to the agents of Netter (YC P26). During my internship at AMOLF (Amsterdam), I wrote an algorithm that made the cover of Nature. The lab was drowning in data: a single fungus generated ~700 GB of microscope images in two months, and a full experiment...
- LinkedIn
People overuse LLMs.
People overuse LLMs. One of the most common misconceptions in AI today is to assume that every intelligent system should be an LLM. LLMs are extraordinary, but they are language models i.e optimized to understand and generate sequences of tokens. The fact that they can answer...
- LinkedIn
One month ago, Andrej Karpathy (founding member at OpenAI) posted something that stormed Twitter about LLM Knowledge Bases, and it perfectly illustrates what we are building.
One month ago, Andrej Karpathy (founding member at OpenAI) posted something that stormed Twitter about LLM Knowledge Bases, and it perfectly illustrates what we are building. The idea is simple: you dump raw data sources, papers, tables, repos, and let an LLM turn all of it...