OmniAI Revolutionizes Business Data for Enhanced AI Integration

Many companies find it challenging to unlock the full potential of their data. Forrester reported several years ago that a staggering 60% to 73% of data in the average business remains untouched for analytical purposes. This is largely due to data being siloed or restricted by technical and security constraints, which complicates the application of analytical tools.

Anna Pojawis and Tyler Maran, engineers with experience at Y Combinator-backed startups Hightouch and Fair Square, recognized the widespread barriers preventing businesses from accessing their analytics capabilities. They were motivated to tackle the data value dilemma after realizing that numerous organizations were effectively "locked out" of effective analytics strategies due to engineering challenges.

Maran emphasized, “A large portion of the market, particularly in regulated sectors like healthcare and finance, faces hurdles with data analytics. Most corporate data doesn't fit neatly into databases—it's comprised of sales calls, documents, Slack messages, and more. Therefore, standard data models often fall short for large organizations.”

In response, Pojawis and Maran launched OmniAI, a suite of tools designed to convert unstructured enterprise data into formats that data analytics applications and AI can effectively utilize.

OmniAI integrates directly with various data storage solutions and databases, such as Snowflake and MongoDB, preparing the data for analysis. Businesses can then deploy their chosen models—such as large language models—on the clean data. Importantly, OmniAI processes all operations in the customer’s cloud environment, its private cloud, or on-premises, enhancing security, as noted by Maran.

Maran stated, “We envision that large language models will be critical to a company's infrastructure in the coming decade. It makes perfect sense to have everything consolidated in one location.”

OmniAI comes equipped with out-of-the-box integrations featuring popular models like Meta’s Llama 3, Anthropic’s Claude, Mistral’s Mistral Large, and Amazon’s AWS Titan. These models facilitate varying use cases, including the automatic redaction of sensitive information and the development of AI-driven applications. Clients engage with OmniAI through a software-as-a-service agreement, allowing them to manage models within their own infrastructure.

While still in its infancy, OmniAI recently secured a $3.2 million seed funding round led by FundersClub, bringing its valuation to $30 million. The startup proudly reports having ten clients, including Klaviyo and Carrefour, and anticipates reaching an annual recurring revenue of $1 million by 2025.

“Our team is highly efficient within a rapidly evolving industry,” Maran remarked. “We believe that over time, more companies will choose to run models alongside their existing infrastructure, prompting model providers to concentrate on licensing model weights to established cloud services.”