Singapore startup aims to expedite AI adoption for complex business insights with its customizable large language models
Singapore-based AI analytics startup Defog secured $2.2 million in seed funding led by Y Combinator and Script Capital to expedite development of its open-source SQLCoder large language model that can deploy directly on databases to enable faster data analysis by generating answers 80% quicker than manual processes.
Singapore-based AI Analytics Startup Defog – secured $2.2 Million in Funding
Singapore-based AI analytics startup Defog has secured $2.2 million in a seed funding round led by Y Combinator and Script Capital.
Other investors include Hike Ventures, Pioneer Fund, and several angel investors.
Defog aims to help companies accelerate data analysis using its open-source large language model, SQLCoder.
The model can be deployed directly on a company’s database to enable employees to pose questions in plain English and get faster answers than manual analysis.
©Github | SQLCode
SQLCoder’s AI Analytics Capabilities
“SQLCoder can generate answers 80% faster than humans performing manual analysis,” said Defog co-founder and CEO Medha Basu in an interview.
She highlighted the model’s ability to automate many trial-and-error tasks required for statistical analysis.
The fresh capital will expedite the development of SQLCoder and Defog’s Agents platform.
As per Basu, Agents will “empower enterprises to ask even more complex analytical questions using AI.”
Defog’s solutions help companies customize large language models for their specific needs. The startup also assists with cloud or on-premise deployment.
Defog’s Strategy in the Competitive US Market
“Being part of Y Combinator helped us gain traction in the US, as that market adopts AI tech faster than Southeast Asia,” Basu said.
Although the US market will be challenging with Google and OpenAI, Basu is sure that Defog can tailor its large language model to match each client’s particular requirements.
Defog aims to differentiate itself by providing flexibility to modify models as per business requirements rather than offering AI through APIs.
The company also provides task-specific models at lower costs compared to general-purpose models.
As AI adoption grows, startups like Defog are poised to enable more democratized access to AI-powered data analytics for companies.
Its latest funding and focus on product-market fit will help cement its position in this space.
