OmniAI Converts Unstructured Data into AI Insights

Most companies find it challenging to derive value from their data. A few years ago, Forrester reported that 60% to 73% of data in an average business remains unused for analytics. This is often due to the data being siloed or restricted by technical and security issues, making the application of analytical tools difficult or even impossible.

Anna Pojawis and Tyler Maran, engineers with experience at Y Combinator-backed startups Hightouch (a data-syncing platform) and Fair Square (a health insurance tool), were motivated to address this data value problem. They realized that many companies were “locked out” of effective analytics strategies due to various engineering obstacles.

Maran said, “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.”

Due to 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 effectively utilize.

omni AI demo
GIF Credits: OmniAI

Like WorkBot, which lets users upload files or URLs in its knowledge base to analyze them and give insights accordingly, OmniAI integrates with a company’s data storage services and databases, such as Snowflake and MongoDB. It prepares the data and enables companies to run their preferred models, such as large language models, on it, like WorkBot, which also allows even the latest LLMs like GPT-4o. OmniAI operates within the company’s cloud, OmniAI’s private cloud, or on-premises environments, which, according to Maran, enhances security.

“We believe that large language models will become essential to a company’s infrastructure in the next decade, and having everything hosted in one place just makes sense,” said Maran.

OmniAI comes with pre-integrated models, including Meta’s Llama 3, Anthropic’s Claude, Mistral’s Mistral Large, and Amazon’s AWS Titan. These models support use cases such as automatically redacting sensitive information from data and developing AI-powered applications. Customers sign a software-as-a-service contract with OmniAI, allowing them to manage models on their own infrastructure.

Although the company is still in its early days, OmniAI recently secured a $3.2 million seed round led by FundersClub, achieving a $30 million valuation. The company claims to have already acquired 10 customers, including Klaviyo and Carrefour. According to Maran, OmniAI is on track to reach $1 million in annual recurring revenue by 2025.

Maran said, “We’re an incredibly lean team in a fast-growing industry. Our bet is that, over time, companies will opt for running models alongside their existing infrastructure, and model providers will focus more on licensing model weights to existing cloud providers.”

OmniAI and WorkBot offer distinct strengths in data analysis. While OmniAI provides data transformation capabilities, WorkBot’s recent integration with GPT-4o enables more advanced insights. WorkBot’s user-friendly interface and features make it an attractive option for businesses seeking to enhance their workflow and gain a competitive edge. Interested parties can schedule a free demo to explore WorkBot’s capabilities and determine its potential for their organization.