We sat down with Joe Lonsdale (@JTLonsdale) and explained why “Dental Billing” is one of the most compelling & complex applications of LLMs.
- AI Phone calls to insurance companies
- vLLMs to read 300+ page pdfs
- Web agents to navigate insurance portals
- Reasoning models to dispute denials
At DayDream we are transforming American small businesses with AI & allowing dentists to focus on what they love – treating patients.
If you're serious about working on difficult problems, we're hiring for Eng/Ops/Sales roles!
DM me or see https://t.co/oRYSoFgXYS
Over 1 billion PDFs are created every day, but your agents still can’t read them reliably.
Today we’re releasing Parse 2.0, the most accurate document parsing API in the world.
Extend already processes millions of pages daily for leading AI teams like Brex, Mercury, Opendoor, Flatiron Health, and hundreds of others. Now, its even better.
Parse 2.0 is SOTA quality on RealDoc-Bench, our open source benchmark that measures agent success rate on real world docs that agents actually encounter in production.
We trained Parse 2.0 on 1M+ pages of the hardest documents seen in production. Here’s how it stacks up:
- #1 in healthcare, real estate, logistics, and financial services
- 95.7% agent Q&A accuracy on 581 docs (next best: 92%)
- 0.847 F1 on layout (next best: 0.759)
Give it a try today and build production-ready document agents with Extend.
You could pay for fake AI talking head UGC, or you could just do a good enough job that they talk about you for free.
We could just be doing it wrong? 🤷 idk
GPT-5.4 also has a 1M context window, but their evals show that needle-in-a-haystack (MRCR v2) scores 97% at 16-32K tokens, drops to 57% at 256-512K, and just 36% at 512K-1M.
So it's a good idea to compact regularly!
@nateberkopec@scoutapp_ai aah the good old days.. hopefully you use us as a good example 😛
Currently trying to help dentists get paid for their work at https://t.co/CDF3hPLpCp