InstaLILY raises $60M for AI software-building tool

InstaLILY, an enterprise automation startup, announced the close of a $60 million（約96億円） Series B funding round, bringing total capital raised to almost $100 million（約160億円）. The round was led by Energize Capital with participation from previous investor Insight Partners and new backers Home Depot Ventures and United Rentals.

Simultaneously, the company unveiled Lily, a new tool designed to help organizations build, deploy, and maintain custom software for business operations. Lily is described as an "AI forward-deployed engineer" that works by being trained on an organization's business processes, enabling it to develop software applications tailored to each company's specific needs. Uses include building applications for pricing quotes, logistics planning, identifying sales opportunities, and serving as a diagnostic assistant for field technicians at remote locations. Once deployed, Lily integrates into an organization's existing software and systems, allowing it to adapt as data and processes evolve.

Founder and CEO Amit Shah explained the motivation behind Lily: each organization performs work that is unique to its operations and too specific for off-the-shelf software, forcing reliance on legacy systems and manual workarounds. "Lily turns that work into software, and it is running in days, not quarters," Shah said. InstaLILY's broader platform includes InstaWorkers—domain-specific AI agents controlled by InstaBrain, a specialized large language model layer—that assist sales teams with tasks like ranking calls, flagging churn risk, identifying cross-selling opportunities, and drafting quotes. Operations and support teams use them for pricing and inventory questions, coordinating returns, and parsing technical documentation.

The company's growth has been substantial. Revenue increased more than fivefold over the past year, driven by customer successes. InstaLILY highlighted two unnamed examples: a national distributor that identified and pursued new sales opportunities generating over $200 million（約320億円） in new revenue, and an industrial supply firm where Lily automated request-for-quote processes, eliminating hundreds of thousands of hours of manual work. Named customers span construction, logistics, healthcare, and field service sectors, including SunSource, Parts Town, SRS Distribution, United Rentals, ShipStation Global, Henry Schein, and PartsSource. Patrick Garcia, SRS Distribution's chief digital, AI and innovation officer, noted that many AI systems fail at scale when deployed at his company's size due to constant business evolution. "Lily has helped us build the software our teams need while working within the enterprise platforms, governance and processes we've already established," he said.

Looking ahead, InstaLILY plans to expand Lily's capabilities, grow its teams, enter new industries, and build out its data center infrastructure to enable customers to run AI systems in the cloud or on-premises with enhanced security for sensitive data.

InstaLILY operates in the enterprise automation space, targeting companies in physical goods and services industries where workflows are highly specific to each organization. The company's core offering, InstaWorkers, are domain-specific AI agents controlled by InstaBrain, a specialized large language model layer fine-tuned to understand each customer's business nuances. The new Lily tool extends this approach into software development itself, allowing companies to turn undocumented institutional knowledge and manual processes into automated software without relying on off-the-shelf products or lengthy implementation timelines.

The fundraise and customer results reflect strong demand for this approach. One unnamed national distributor identified and pursued sales opportunities worth over $200 million（約320億円） in new revenue using the platform; an industrial supply firm automated its request-for-quote process, eliminating hundreds of thousands of hours of manual work. These outcomes suggest that the market recognizes the value of AI tools that can adapt to enterprise-specific requirements and constraints. SRS Distribution's chief digital officer noted that Lily succeeded where many AI systems fail at scale—by working within the organization's existing enterprise platforms and governance structures rather than requiring wholesale process change.