OmniAI transforms business data for AI

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The majority of companies struggle to extract value from their data. Several years ago, Forrester reported that between 60% and 73% of data belonging to the average business goes unused for analytics. That’s because the data’s siloed or otherwise pigeonholed by technical and security considerations, making it difficult — if not impossible — to apply analytical tools.

Anna Pojawis and Tyler Maran, engineers who previously did stints at Y Combinator-backed startups Hightouch (a data-syncing platform) and Fair Square (a health insurance tool), were inspired to try their hands at solving the data value problem after discovering that many companies had been “locked out” of analytics strategies due to the engineering roadblocks.

“We’ve found that a significant part of the market, especially those in regulated industries like healthcare and finance,” have struggled with data analytics, Maran told TechCrunch. “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.”

So Pojawis and Maran founded OmniAI, a set of tools that transform unstructured enterprise data into something that data analytics apps and AI can understand.

OmniAI
Image Credits: OmniAI

OmniAI syncs with a company’s data storage services and databases (e.g., Snowflake, MongoDB, etc.), preps the data within and allows companies to run the model of their choice — for example, a large language model — on the data. OmniAI performs all of its work in the company’s cloud, OmniAI’s private cloud or on-premises environments, delivering ostensibly improved security, according to Maran.

“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,” Maran said.

Out of the box, OmniAI offers integrations with models, including Meta’s Llama 3, Anthropic’s Claude, Mistral’s Mistral Large and Amazon’s AWS Titan for use cases like automatically redacting sensitive information from data and generally building AI-powered applications. Customers sign a software-as-a-service contract with OmniAI to enable management of models on their infrastructure.

It’s early days. But Omni, which recently closed a $3.2 million seed round led by FundersClub at a $30 million valuation, claims to have 10 customers already, including Klaviyo and Carrefour. Annual recurring revenue is on track to reach $1 million by 2025, Maran said.

“We’re an incredibly lean team in a fast-growing industry,” Maran said. “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.”

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