OmniAI

Omni's open source OCR tool has just crossed 6,000 stars on github! We're thankful for all the community contributions, and super excited to keep shipping new features. So far this month we have added: - Intelligent page chunking for RAG. - Support for auto correcting page orientation (quality goes way up when all the pages are facing the right way). - The ability to pass in fine tuned models. - A lot more image preprocessing options (trim whitespace, improve contrast, etc.) Give us a star on github to follow along with the journey.

🎉 1 month into my journey at OmniAI! Crazy growth in a month: 🚀 Zerox, our open-sourced vision-based OCR: 1k → 6k stars 🚢 new features are shipped every 2 days 🔄 migrated to k8s because of large data volumes 💰 launched our pricing page 📈10x inbound leads (and closing more deals!) This is just the beginning! And yes, we are HIRING! We're looking for founding engineers and growth/content designers. DM me if you like building an unicorn together 🦄

Welcome, Mark (Kailing) Ding! We’re super excited to have you on the OmniAI team! 🔥 Mark co-founded Brewit, a YC startup focused on AI data analytics, and previously worked at Tesla as an engineer and data scientist. In just two weeks, Mark has already rolled out multiple features our customers requested. He's an incredible engineer and crazy fast learner! Can’t wait to see all the amazing things you’ll build with us!

We're hiring a Designer + Content engineer at OmniAI! You may have noticed, we're on Linkedin all the time! It's one of our strongest channels, and we'd really love to level up some of our content / branding. Plus expand to new channels. Types of things you'll be working on: - Landing page + blog + testimonials + success stories - Linkedin content (banners, product videos, etc.) - Ad content - Swag, conference banners - Monthly newsletter + changelog - and a lot more! We're looking for people with an engineering mindset, but slightly better design skills than my microsoft paint drawings (which I legitimately use every day 🤣). Especially interested if you've done some technical content writing before. I'll drop the full details below. Please leave comment if you're interested, or if you know someone who would fit this role!

Welcome to the team, Xiangyi Li!

We use OmniAI to do market research for OmniAI! One of our top use cases is companies with a lot of call data (think Gong, Aircall, Dialpad, etc.). So naturally we want to find all the companies that might be a good fit for Omni. So I started off by getting a list of ~750 customer success stories from all of these call providers. All I added to Omni was the URL for each story, and now I have a full dataset of: - Company name, - Website - Summary - Name / title of the decision maker - Call Provider - Industry - Internal use case (i.e. sales, customer success, etc.) - Main reason they switched to this provider - Size of the company And this all comes from a single url.

We’ve gotten this ask from a handful of customers, so we built it into OmniAI. And now we use it daily as well! Our new AI scraper tool makes it super easy to pull content and research any website. At scale. Examples of what you can ask: - Summarize your customer base 🕵️♂️ - Extract job posts 📝 - Pull product descriptions from competitors listings 📦 And so much more! Reach out if you have a lot of sites you need to research.

Our open source OCR tool hit 1,000+ github stars in 7 days! ⭐️ And what started as a fun weekend hack has already made it into production use cases. But more important than github stars, we have some people making serious contributions. And later today, we'll be releasing our Python library! 🐍 Now I really don't know python, so I had no plans of expanding past the NPM package. But because we made this tool open source, we're able to expand and add features way faster than we could do this ourselves. Plus you really can't have an AI tool without a python version 😆

New privacy features coming to OmniAI this week! 🔐 Here's a peek at the secret sauce. If you're in a regulated industry (AI applications or not) PII redaction is going be best practice. But simple redaction isn't going to cut it for LLM applications. The models need context to function correctly. i.e. replacing a user's name with "**** *****" is going to produce some unpredictable results. Instead we create a lookup table that substitutes the PII for a semantically similar value. That means `Dan Smith` is substituted for a randomly generated `John Baker` at query time. And the real user information is stored in a secure fashion. And the same substitution is applied as the data comes back from the model. Because we know `John` is a substitution for `Dan`, we're able to swap out response values so the user gets the expected output.

We're hiring!