Description
We are a well-funded pre-seed stage startup with an aim to reorganize the world's information ???? The search engines we know and love are well-suited for consumer applications, but they are not designed for enterprise use cases.
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Too many office hours are spent doing repetitive web research ???? which requires basic reading and writing comprehension.
Up until now, these tasks have been just out of reach from automation, but with the recent advancements in language modeling, they are now possible.
Our first product is a customer analytics platform for enterprise revenue teams.
Our customers love our product because it saves them hours of tedious work reading through the text to find the insights they need ???? As such, we've been able to grow organically through word-of-mouth referrals.
We are currently preparing for 10X users to onboard.
On a high level
- our data pipeline takes a configuration from our users about target companies and questions they need to be answered, ingests natural language data from the web, and extracts snippets of information about the target companies that answer our users' research questions ❓ The engineering roadmap for the next 6 months includes implementation of more sophisticated text analytics and processing features, improving the efficiency and scalability of our data pipeline, and exposing more filters and controls to our users via our UI.
Our stack is PostgreSQL, Python, GraphQL, React & Typescript.
We are a small team of physicists and computer scientists (Cambridge, Imperial, Palantir, CERN) based in London.
We will be operating remotely until it is safe to consider an alternative.
We intend to open an office in London when it is safe to do so, but we will be flexible to remote