3...2...1... Liftoff, Today, we are excited to introduce Anote to the world. Anote is a general purpose artificial intelligence startup in New York City. In the vision to make AI more accessible, we are releasing 2 core products: 1) Sababa - Sababa is an autonomous AI agent that, on trigger of natural language query, can be used to semi-autonomously, precisely search for and email millions of people. This has been used for a variety of applications: Sales: I want to sell Sababa to people who work as Head of Sales in the Insurance industry, Hiring: I want to find a job as a Software Engineer at Amazon in San Francisco, Upon a one line command, the AI can figure out who to specifically reach out to, and effectively send targeted, tailored campaigns of emails to new leads that many of our users previously never had access to. In our enterprise version, we have advanced capabilities including but not limited to: Marketing: I want to advertise my pet company to people who are democrats who own a dog with children between 5 and 10 years old, Companies: I want to find all companies in the finance industry that have between 50 and 250 people that are interested in document processing. 2) Anote - The Anote platform, pioneered by human centered AI, actively learns from human feedback to make AI algorithms like GPT-4, Bard and Claude and techniques like RLHF, Fine-Tuning and RAG, perform better for specific use cases over time. Over time, we are able to provide more tailored answers to questions, category predictions and entities found because our platform enables AI models to actively learn and rapidly improve from the knowledge of domain specific subject matter experts. On the Anote platform, users can upload unstructured data like PDFs, TXTs, DOCXs, PPTXs, scrape HTML files from websites, or upload structured data like CSVs. Users can connect to any dataset on the hugging face dataset hub, or integrate with external data sources like Reddit, S3, Notion, Asana, Github, Snowflake, Twitter. After the user customizes their requirements (adding the questions, categories or entities they care about), the AI model is able to actively learn from people with just a few interventions to improve model performance (think hundreds of rows labeled, rather than millions required for re-training LLMs). Users can download the resulting CSV of actual and predicted results, as well as export the updated AI model to make real-time, improved model inference and predictions via the call of an API. This technology has already solved problems in a variety of applications: - Extracting Information from 10-Ks and Earnings Calls in Finance - Summarizing Medical Charts and Labeling Unstructured Data in Healthcare - Answering Questions on Contracts and Case Studies in Legal Tech - Accurately Categorizing Text data into ~400 Categories in Ad Tech, Competitive Intelligence, and Social Media Analytics Get started now: anote.ai Learn more here: docs.anote.ai