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Millions of people are looking at JMail to understand what was released in the Epstein files
Here's what that looked like behind the scenes:
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Adit
1,281 posts
- if your cto works with good posture you should start polishing your resume
- you will never catch me sitting in a photo again
from the video it looks like they're almost the same height... this framing is diabolical 😂 - I’m thrilled to announce @reductoai’s $75M Series B led by @a16z, which brings our total funding to $108M. Just five months after our Series A, we've surpassed 1 billion pages processed and grown our monthly volume 6x. We now process hundreds of millions of pages every month for
00:00 - We raised a $24.5M Series A led by @benchmark, bringing total funding to $33M!🚀 Last year we set out to define the state of the art in document processing. Today, companies like Vanta, Airtable, and ScaleAI trust @reductoai to ingest hundreds of millions of documents. (1/7)
- We landed a million dollar contract with a trillion dollar enterprise in our first year @reductoai. The sales process took 154 days, 20+ hours of meetings, and a lot of emails. I wrote a blog post outlining each step and what we learned. Full blog and summary in thread 👇
- happy halloween from the founders of @reductoai
- YC tells you to hire your smartest friends but our smartest friends keep getting into YC 🥲
- Earlier today Mistral released a new OCR api that claims to be state of the art. They didn’t release their benchmarks so we tested it against Gemini ourselves. Mistral reported its OCR as better than Gemini. Our testing showed the opposite. Full blog post in the replies!
- Today, @reductoai is helping hundreds of AI teams ingest tens of millions of pages every month, and we’re excited to announce that we’ve raised an $8.4M seed round led by @firstround to continue on our mission of making human data LLM-ready. (1/7)
- A YC team in healthcare had asked us to help with doc processing a few months ago, and we were honestly shocked at how messy their PDFs were Medical docs are filled with messy handwriting and scans that make it impossible to get LLM-ready data
