Solving the Data Value Problem: OmniAI’s Innovative Approach
In today’s data-driven world, companies are constantly seeking to extract value from the vast amount of information at their disposal. However, a significant number of businesses face challenges when it comes to utilizing their data effectively. According to a report by Forrester, between 60% and 73% of data within the average organization goes unused for analytics purposes. This untapped potential is often due to data being siloed or inaccessible due to technical and security constraints, preventing the application of analytical tools.
Recognizing this problem, Anna Pojawis and Tyler Maran, experienced engineers who have worked with Y Combinator-backed startups, decided to tackle the data value issue head-on. After discovering that many companies were “locked out” of analytics strategies due to engineering roadblocks, they founded OmniAI.
Pojawis and Maran realized that a significant portion of corporate data does not fit neatly into traditional databases. Sales calls, documents, and Slack messages are just a few examples of the unstructured data that businesses struggle to analyze effectively. Off-the-shelf data models often fall short in meeting the needs of these companies, particularly those in regulated industries such as healthcare and finance.
To bridge this gap, OmniAI offers a set of tools that transform unstructured enterprise data into a format that can be understood by data analytics applications and artificial intelligence (AI) systems. By syncing with a company’s data storage services and databases, OmniAI prepares the data for analysis and allows companies to run their chosen models on the transformed data. All of this is done securely within the company’s cloud, OmniAI’s private cloud, or on-premises environments.
One key aspect that sets OmniAI apart is its focus on large language models. The founders believe that these models will become essential infrastructure for companies in the coming decade. By hosting everything in one place, OmniAI aims to provide convenience and improved security for its customers.
OmniAI already boasts an impressive list of customers, including Klaviyo and Carrefour. It offers integrations with notable models such as Meta’s Llama 3, Anthropic’s Claude, Mistral’s Mistral Large, and Amazon’s AWS Titan. These integrations enable use cases like automatically redacting sensitive information from data and building AI-powered applications. Customers enter into a software-as-a-service contract with OmniAI to manage the models on their infrastructure.
While OmniAI is still in its early stages, it has recently secured $3.2 million in seed funding led by FundersClub, valuing the company at $30 million. With its lean team and a rapidly growing industry, OmniAI is poised for success. Maran predicts that annual recurring revenue will reach $1 million by 2025.
Looking ahead, OmniAI believes that companies will increasingly choose to run models alongside their existing infrastructure. This trend may lead model providers to focus more on licensing model weights to existing cloud providers. As the demand for data analytics and AI continues to surge, innovative solutions like OmniAI are likely to play a crucial role in helping businesses unlock the true value of their data.