AI Library Raises $560,000 in Pre-Seed Funding at $7.5 Million Valuation Cap
Its platform enables enterprises to accelerate deployment timelines, improve operational efficiency, and reduce software delivery costs through continuously learning AI-driven systems.
AI-native software delivery startup AI Library has raised $560,000 in a pre-seed funding round at a valuation cap of $7.5 million from a group of investors.
The company said the fresh capital will be used to strengthen product development, expand market presence, and accelerate research and development initiatives.
Founded in November 2023 by Arani Chaudhuri and Rajeev Singh, AI Library is building an outcome-based AI-native software delivery platform focused on automating the software development lifecycle through AI agents supported by human oversight.
The Bengaluru-based startup develops what it calls “autopilots” for enterprise software delivery, helping organisations move from AI experimentation to measurable business outcomes across functions such as finance, operations, sales, and customer support.
According to the company, its platform enables enterprises to accelerate deployment timelines, improve operational efficiency, and reduce software delivery costs through continuously learning AI-driven systems.
AI Library has also introduced AI Library MCP, a unified infrastructure layer designed to simplify enterprise AI deployments by enabling structured access to tools, workflows, APIs, and enterprise data systems for AI agents.
The startup claims its infrastructure helps reduce fragmented integrations, minimise redundant AI processing, and improve reliability for enterprise-scale AI deployments.
AI Library says it has already deployed solutions for enterprises including Tally Solutions, The Times Group, Burger Singh, and DeKoder, supporting use cases ranging from finance automation to AI-led sales workflows.
The startup operates in the rapidly growing enterprise AI automation segment, where companies are increasingly investing in AI-native infrastructure to improve software delivery, operational efficiency, and business productivity.