OmniAI: Revolutionizing Data Analytics for Enterprises

A large number of companies are grappling with the challenge of extracting value from their data. According to a Forrester report, between 60% and 73% of data in the average business remains untapped for analytics. The main barriers include data being siloed or restricted due to technical and security concerns, making it challenging to utilize analytical tools effectively.

Engineers Anna Pojawis and Tyler Maran, who have previously worked at Y Combinator-backed startups Hightouch and Fair Square, aimed to tackle this issue after noticing that many businesses were "locked out" of analytics due to engineering hurdles.

Maran explained to TechCrunch, “We’ve found that a significant part of the market, especially those in regulated industries like healthcare and finance have struggled with data analytics. The majority of corporate data doesn’t fit into a database today; it’s sales calls, documents, Slack messages and so on. And, given the scale of these companies, off-the-shelf data models are typically not sufficient.”

To address this, Pojawis and Maran founded OmniAI, a suite of tools designed to convert unstructured enterprise data into formats that data analytics applications and AI can process.

OmniAI integrates with a company’s existing data storage services and databases, such as Snowflake and MongoDB, and prepares the data for analysis. It allows companies to run models, including large language models, on their data, enhancing security by operating within the company’s cloud, OmniAI’s private cloud, or on-premises environments.

OmniAI supports various models, including Meta’s Llama 3, Anthropic’s Claude, Mistral’s Mistral Large, and Amazon’s AWS Titan, for tasks such as automatic redaction of sensitive information and building AI-powered applications. Customers subscribe to OmniAI’s software-as-a-service model to manage these models on their infrastructure, streamlining their data analytics capabilities.

Source: Kyle Wiggers / TechCrunch