“Turn Any App Agentic Within 24 Hours” Says Adopt AI With $6M Backing

As large language models continue to gain traction in enterprise applications, companies are beginning to look beyond text generation and chatbot support. One area drawing increasing attention from product teams is agentic AI where software components that can automate tasks and interact with other systems using natural language inputs.

Adopt AI, a startup based in San Francisco and Bengaluru, is aiming to make that transition easier for companies that don’t have months of engineering bandwidth to retool their existing platforms. The company has launched out of stealth with a $6 million seed round led by Elevation Capital, with participation from Foster Ventures, Powerhouse Ventures, Darkmode Ventures, and several angel investors.

Founded by Deepak Anchala, Rahul Bhattacharya, and Anirudh Badam, Adopt AI has built a no-code platform designed to help businesses integrate intelligent agents into their applications. The goal is to reduce the development time for building agent interfaces from months to hours, particularly for SaaS and B2C firms in sectors like banking and healthcare where user workflows are often complex and fragmented.

“In the agentic AI world, applications are coming closer to humans with natural language,” said Anchala in an interview. “Applications as they stand today will lose out to agentic AI companies unless they change. So we are building an agentic layer for them to turn any application into an agentic one—within 24 hours.”

From Slintel to Adopt

This isn’t the founding team’s first software venture. Anchala and Bhattacharya previously built Slintel, a sales intelligence platform that raised $25 million, grew to more than 100 employees, and served over 300 customers before being acquired by go-to-market platform 6sense in 2021. Their new company is focused on helping businesses adapt their legacy applications to a new interface paradigm that relies on natural language rather than fixed navigational flows.

The technology behind Adopt is designed to integrate with existing applications and automatically map their workflows. One of its key products, Agent Builder, allows users to generate a set of software actions—such as submitting forms, retrieving data, or executing workflows by analyzing how users interact with the app. These actions can then be embedded into a conversational interface called Agent Experience, which allows users to complete tasks through plain language commands either within the app or via external channels.

A Technical Shortcut

Anchala said that while many companies see agent-based interaction as a near-term priority, implementing it has proven difficult. In practice, converting a product into an agentic interface requires navigating undocumented APIs, managing front-end interactions, and maintaining performance all while ensuring responses remain accurate and context-aware.

“There’s a growing interest from product and technology teams, but the development overhead is high,” Anchala said. “Even with the right talent, it can take six months or more to build this in-house.”

Adopt’s approach is to handle the underlying orchestration, including authentication layers, workflow understanding, and multi-step action execution. It also offers testing and monitoring tools to evaluate how the agent performs and whether it introduces unexpected behavior. According to the company, this helps businesses avoid building a parallel system just to support natural language interaction.

The Engineering Team

Adopt employs 16 people across the U.S. and India. Its Bengaluru office includes full-stack developers, product managers, and designers, while its U.S. team focuses on AI engineering. Chief AI Officer Anirudh Badam previously worked on AI and machine learning systems at Microsoft’s Seattle office, and founding engineer Vijay Sagar spent more than a decade at Google working on production-grade ML infrastructure.

The company’s current customers are part of an early access program that allows them to test Adopt’s agent capabilities and co-develop new features. Anchala said this has helped refine the product around common implementation challenges faced by mid-size software companies, particularly those in regulated industries.

Market Dynamics

Several large technology companies including Microsoft, Meta, and Anthropic have announced efforts in agentic AI, though these are mostly focused on horizontal deployment or foundational models. Anchala believes there’s still a gap between what those platforms offer and what enterprise applications need.

“Our focus is on the agent layer within applications,” he said. “Most large players will go broad, but businesses still need deep integration to get actual work done through agents.”