InstaLILY Raises $60M Series B to Expand Enterprise AI Workflows

InstaLILY has raised a $60M Series B, bringing the company's total funding to nearly $100M. The New York company, founded in 2023 by Amit Shah and Sumantro Das, is building Lily, an AI Forward Deployed Engineer designed to learn business workflows and run work across the enterprise systems companies already use.

The financing gives InstaLILY more room to expand Lily into additional industries, strengthen its AI infrastructure, and grow the team. More importantly, the round shows where enterprise AI capital is moving: away from demo-friendly assistants and toward software that can handle operational complexity inside the physical and regulated economy.

What Happened

InstaLILY announced the Series B alongside the launch of Lily as what it calls the world's first AI Forward Deployed Engineer. The round was led by Energize Capital, with participation from Insight Partners, Home Depot Ventures, and United Rentals. The company says Lily learns how a business works, builds the software the work needs, and runs it across ERP platforms, CRM systems, email, internal applications, and the other tools that keep enterprise operations moving.

That framing matters because InstaLILY is not pitching another thin chatbot layer on top of existing software. The company is trying to turn the forward-deployed engineer model into repeatable enterprise infrastructure, where AI studies the work, builds missing workflows, coordinates across systems, and continues improving as business conditions change.

The investor group reinforces that thesis. Energize Capital led the round, Insight Partners continued its support after leading InstaLILY's earlier Series A, and strategic investors Home Depot Ventures and United Rentals joined from industries where fragmented operational systems are not an abstract pain point.

Why This Matters

Enterprise software has spent decades making individual departments more efficient while making the business as a whole harder to understand. Sales teams live in one system, operations in another, finance somewhere else, and customer service in its own stack, leaving employees to carry the connective tissue through inboxes, spreadsheets, tribal knowledge, and manual follow-up.

That is the gap InstaLILY is attacking. Lily focuses on the work itself rather than the application where one slice of the work happens, giving the product a different angle than copilots built primarily to assist users inside a single interface.

The distinction is not cosmetic. Businesses rarely stall because they need another dashboard. They stall because context, approvals, exceptions, and decisions get trapped between systems that were never designed to understand one another.

Market Context

The broader enterprise AI market is becoming more practical. Buyers have had enough time with generative AI to separate impressive demos from tools that can survive real workflow pressure, and the next wave of adoption will likely reward companies that can produce measurable operational outcomes.

That is why InstaLILY's focus on the physical and regulated economy is compelling positioning. Distribution, construction, field service, healthcare operations, logistics, and similar markets tend to run on complex processes, legacy systems, high exception volume, and institutional knowledge that does not fit neatly into a single SaaS workflow.

Amit Shah's background adds context to the bet. Before founding InstaLILY, he served as President at 1-800-Flowers, giving him firsthand exposure to the kind of distribution-heavy, systems-intensive operations where employees often lose time translating work across tools.

Competitive Landscape

InstaLILY sits in a crowded enterprise AI market, but its wedge is execution rather than conversation. While many companies compete on model access, copilots, or single-application automation, InstaLILY is trying to build a system that understands how work moves across the entire enterprise environment.

That makes the strategic investor participation more interesting. Home Depot Ventures and United Rentals are not just financial logos. They represent industries where quoting, routing, inventory, field service, approvals, and customer follow-up become expensive when the systems underneath them do not communicate cleanly.

The company also benefits from a simple market truth that enterprise buyers understand immediately. Rip-and-replace transformation is expensive, slow, and risky, so AI that can work inside existing infrastructure has a cleaner adoption story than software that asks customers to rebuild their operating stack first.

What This Signals

Funding announcements often reveal as much about investor conviction as founder ambition. In this case, a $60M Series B and nearly $100M in total funding suggest investors see a major opportunity in AI that connects fragmented workflows rather than merely producing better text.

That is an important shift for the category. Enterprise AI's long-term value may come less from systems that sound intelligent and more from systems that can interpret business context, coordinate actions, and improve execution inside messy operating environments.

For operators, the signal is straightforward. The market is beginning to reward AI companies that understand work at the process level, not just the interface level, and that could push the category toward more durable infrastructure.

The Bigger Industry Shift

The AI conversation is becoming less theatrical because enterprise buying decisions eventually drag every technology back to reality. Executives want fewer disconnected workflows, operators want fewer repetitive handoffs, and technology leaders want AI that fits into existing infrastructure without demanding another costly transformation program.

InstaLILY's raise sits directly inside that shift. If Lily can consistently learn how businesses operate, build the missing workflow layer, and run inside the systems customers already depend on, the company is not selling a novelty. It is selling a way to make enterprise software feel less broken.

That is why this round matters beyond the headline number. In a market crowded with companies teaching AI to talk, InstaLILY is trying to teach AI how work actually gets done, and that is a much more valuable conversation.