OmniAI Leads the Charge in Harnessing Business Data for AI-Driven Insights

Many companies continue to face significant challenges in extracting value from their vast reservoirs of data. A few years ago, a Forrester report highlighted that between 60% and 73% of all data owned by businesses remains unused for analytics. This underutilization often results from data being siloed due to technical and security constraints, which severely limits the application of advanced analytical tools.

Engineers Anna Pojawis and Tyler Maran, who previously worked with Y Combinator-backed startups Hightouch and Fair Square, have set out to address this pervasive issue. They observed that many firms are essentially "locked out" of effective analytics strategies because of engineering bottlenecks.

In an interview with TechCrunch, Maran explained, "We’ve found that a significant part of the market, especially those in regulated industries like healthcare and finance, have struggled with data analytics." He further noted that "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 tackle these challenges, Pojawis and Maran co-founded OmniAI, a company dedicated to transforming unstructured enterprise data into formats that are compatible with data analytics applications and AI technologies. OmniAI connects with an organization's data storage services and databases, such as Snowflake and MongoDB, to prepare the data for analysis. The company enables businesses to run their preferred models, including sophisticated language models, on this data. OmniAI performs all its operations either within the company's cloud, OmniAI’s private cloud, or on-premises environments, which Maran claims offers significantly enhanced security.

Maran shared his vision for the future, stating, "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."

From the get-go, OmniAI has provided integrations with various models such as Meta’s Llama 3, Anthropic’s Claude, Mistral’s Mistral Large, and Amazon’s AWS Titan. These models facilitate applications such as automatically redacting sensitive information from data, thus aiding in the creation of AI-powered applications. Customers engage with OmniAI through a software-as-a-service contract, which allows for the management of these models on their infrastructures.

Despite its recent inception, OmniAI has successfully closed a $3.2 million seed funding round led by FundersClub at a $30 million valuation. The company already boasts a client roster that includes names like Klaviyo and Carrefour, with projections pointing to an annual recurring revenue of $1 million by 2025.

"We’re an incredibly lean team in a fast-growing industry," Maran commented. "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's approach exemplifies a forward-thinking strategy to make business data not only more accessible but also more actionable through advanced AI integration, potentially setting a new standard for data utilization across industries.