How Picarro Turned Cloud Savings into AI and Security Investment

When Parag Jain took on a cloud and infrastructure optimization effort at Picarro, the goal wasn’t simply to spend less. It was to make the company’s technology foundation more efficient—and put the savings to work on priorities that could help the business move forward.

Over 12 months, Jain led a re-architecture and optimization of Picarro’s AWS environment. The work generated approximately $500,000 in savings, which the company reinvested in digital transformation, including AI, security, and enterprise platforms.

A deliberate approach to cloud optimization

Jain described the effort as a cycle of discover, analyze, act, and measure. The team began by identifying lower-risk opportunities it could address internally, including reducing costs associated with end-of-life software support.

From there, Picarro consolidated parts of its U.S. and European footprint and reorganized database and compute resources around customer needs. Rather than applying the same uptime requirements everywhere, the team considered where service levels mattered most—for example, regions with more vehicles operating and greater need for supporting infrastructure.

The team also evaluated vendor recommendations instead of accepting them by default. Jain described comparing options such as AWS Graviton and AMD to make decisions based on the company’s needs and costs.

Putting the savings toward AI

One result of the optimization effort was the ability to fund new initiatives without treating AI as a separate budget request. Picarro introduced Microsoft Copilot within its existing Microsoft 365 environment, which already aligned with the company’s AI governance policies and zero-trust architecture.

Jain said the rollout reached 88% utilization across the Microsoft 365 suite. He also framed the initiative as part of a broader shift: helping IT move from a reactive cost center toward a more strategic role in enabling the business.

What comes next: governing AI agents

Picarro’s next focus is centralized governance for AI agents. As organizations adopt more tools and agents, Jain noted, data can move between systems in ways that are difficult to observe and manage.

The company is working toward a “control tower” approach to identify, measure, and address agent activity across the organization. The aim is to reduce shadow AI and give the business better visibility and control as its use of AI expands.

For Jain, the project’s significance lies not only in the savings, but in how those savings created room to modernize. By pairing cloud optimization with reinvestment and governance, Picarro is using infrastructure work to support a broader digital transformation.