Consolidated seven data platforms onto one platform
Supports 40% annual session data growth with high performance and simple scaling
Delivers fast AI insights through Gemini models
Migrated data without user disruption
Transitioned data analysts to data engineering
ChargePoint is consolidating its global EV charging data lake onto the Snowflake AI Data Cloud, running on Google Cloud and using Gemini models to deliver instant, natural-language analytics leveraging Snowflake data to fleet managers, end customers, and charging operators.
ChargePoint is consolidating its global EV charging data lake onto the Snowflake AI Data Cloud, running on Google Cloud and using Gemini models to deliver instant, natural-language analytics leveraging Snowflake data to fleet managers, end customers, and charging operators.
Eliminating data silos to power the
future of electric mobility
We needed a platform built for infinite scale to handle a 40% year-over-year growth in charging session data. Moving Snowflake to Google Cloud eliminated infrastructure maintenance overhead and gave us the capability to power expansion without disrupting performance.
Jordan Toor
Principal Software Engineer, ChargePoint
As electric vehicle adoption accelerates across North America and Europe, ChargePoint has become a major EV charging hardware and software platform provider. Beyond manufacturing home, commercial, and fleet hardware, ChargePoint’s key differentiator lies in its cloud-connected software network. The platform supports first- and third-party chargers, enables network roaming, and delivers waitlist management and fleet dispatching for charge point operators, auto manufacturers, and drivers.
Supporting a rapidly expanding footprint created technical challenges, with ChargePoint facing a 40% year-over-year surge in charging session data and intelligence requirements. Historically, the company's data was fragmented across seven systems.
The legacy setup slowed query times, increased maintenance needs, and frustrated internal teams attempting to access critical data. ChargePoint needed a unified data architecture that could handle seamless scale without hurting performance. It also wanted to free engineers from infrastructure maintenance to focus on product innovation.
Applying AI with Gemini and Snowflake
on Google Cloud
When first building the Data Assistant, we tested different models, but everything changed when we switched to Gemini. We just changed the model, and suddenly it worked seamlessly.
Paul Giles
Data Engineering, ChargePoint
To overcome scaling hurdles, ChargePoint consolidated its fragmented data systems onto the Snowflake AI Data Cloud.
"Before deploying Snowflake, our data was spread across many systems, creating slow queries and tough user experiences," says Paul Giles, Data Engineering, ChargePoint. "Moving to a managed, best-in-class platform eliminated that overhead and gave us a unified solution. We can scale massive amounts of data without worry."
To accelerate its advanced AI initiatives, ChargePoint chose to run Snowflake on Google Cloud infrastructure, worked closely with Google AI teams to bring its unified data and Gemini models into the same ecosystem. Running Snowflake on Google Cloud eliminated the latency and cost of transferring data across regions. It also enables direct, native access to Gemini models.
"We needed a platform built for infinite scale to handle a 40% year-over-year growth in charging session data," says Jordan Toor, Principal Software Engineer, ChargePoint. "Moving Snowflake to Google Cloud eliminated infrastructure maintenance overhead and gave us the capability to power that expansion without disrupting performance."
By running Snowflake’s AI Data Cloud on Google Cloud, ChargePoint was able to deliver key capabilities, including a new natural language Data Assistant embedded directly within the ChargePoint application. Built with Gemini Flash and Pro models, the Data Assistant allows workplace charging administrators, fleet managers, and commercial operators to ask intuitive questions in plain language.
Gemini translates those natural language requests into complex data queries against Snowflake’s unified dataset, conducts automated safety checks, and returns real-time visualizations and charts. Customers can quickly understand their uptime percentages, identify high-traffic chargers, and optimize fleet routing without needing a dedicated data science team or manual data downloads.
"When first building the Data Assistant, we tested different models, but everything changed when we switched to Gemini," says Giles. “We just changed the model and suddenly it worked seamlessly. The speed and accuracy of Gemini are amazing."
Transforming customer insights and accelerating operational scale
ChargePoint has seen strong value in running Snowflake on Google Cloud. The high speed of Gemini models enables the Data Assistant to parse intent and deliver complex analytics in seconds so charge point operators have unprecedented visibility into their networks.
Externally, customers who previously struggled to parse raw data about vehicle charges and other details can now use the app to find answers on their own about charging health, usage rates, and recommended maintenance.
Internally, the transition to self-service analytics has significantly shifted ChargePoint’s technical workforce. Data analysts who spent their days manually building reports for internal stakeholders have transitioned into full-fledged data engineers focused on platform development.
"Natural language processing through Gemini is one of the biggest benefits we’ve seen," says Toor. "It enables workplace charging operators and fleet managers to ask complex questions, get real-time visualizations, and access the exact data to optimize their charging business."
Natural language processing through Gemini is one of the biggest benefits we’ve seen. It enables workplace charging operators and fleet managers to ask complex questions, get real-time visualizations, and access the exact data to optimize their charging business.
Jordan Toor
Principal Software Engineer, ChargePoint
At the same time, the data science team no longer spends valuable cycles building foundational models from scratch. Instead, they can focus on refining algorithms for predictive maintenance innovation.
"Demand for EV charging in North America and Europe is outpacing infrastructure. Our goal is to fulfill that demand across commercial, home, and fleet charging,” says Toor. “Using Google Cloud and Snowflake gives us the speed and runway to power growth from a leading data and AI infrastructure."
ChargePoint is a global leader in intelligent electrification and e-mobility, operating extensive hardware and software solutions across North America and Europe. The company's cloud-connected platform powers commercial, residential, and fleet charging ecosystems, enabling seamless network roaming, dynamic pricing, and fleet management.
Industry: Utilities
Location: United States
Products: Snowflake AI Data Cloud, Gemini, Gemini models
About Google Cloud partner - Snowflake
Snowflake is an AI Data Cloud platform that enables organizations to mobilize, consolidate, and analyze massive datasets across cloud environments with high performance and scale.
