Grid Dynamics Global
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AI-first digital engineering services and technology consulting company founded in Silicon Valley in 2006.
We transform Fortune 1000 enterprises through advanced generative, agentic, and physical AI, data platforms, and cloud-native engineering. ▪️4,000 world-class engineers
▪️HQ in Silicon Valley
▪️Offices in 18 countries
▪️The core expertise: Big Data, Data Science, AI & ML, scalable omnichannel services, DevOps, and cloud enablement
▪️In 2020-2021, Grid Dynamics expanded its global footprint by a
Last week at the AWS offices in New York City, Grid Dynamics brought together senior leaders from banking, capital markets, and wealth management to discuss one of the industry's most pressing questions: how to move AI from experimentation to production in highly regulated environments.
The conversation focused on practical AI implementation across middle- and back-office functions, where firms are looking to drive efficiency, improve decision-making, and modernize operations while meeting increasingly complex governance and compliance requirements.
A key insight came from Henry Garner, CTO for Capital Markets at Grid Dynamics, who highlighted a critical governance component that is missing from many AI deployments today—and why addressing that gap is essential for regulated industries.
The panel discussion that followed explored the realities organizations face when deploying AI at scale, from risk management and compliance to operational governance and accountability.
As Rahul Bindlish, SVP and Global Head of Partnerships and Marketing at Grid Dynamics, noted:
"What we heard in this room just confirms what we are seeing in the industry. While the technology is ready, the frameworks for safely and securely deploying it are still evolving. And that's the problem that we are most focused on solving."
The message was clear: the challenge is no longer whether AI can deliver value. The challenge is creating the governance, control, and operational frameworks that enable organizations to deploy AI with confidence.
Thank you to everyone who joined us for an insightful discussion and shared their perspectives on the future of AI in financial services.
06/05/2026
A huge thank you to everyone who recently joined Grid Dynamics at the AWS offices for our Agentic AI in Alternatives workshop in New York.
We had insightful discussions and strong engagement with senior Wealth Management and Alternatives executives on applying AI in regulated Alternative Investment environments.
Looking forward to continuing the conversation, exploring new collaborations, and sharing details on our upcoming executive-focused events soon.
06/04/2026
Most organizations assume their AI agents are being evaluated. Most are wrong. If your organization is deploying AI agents in production, this is worth your time. https://bit.ly/4wKutWl
As AI agents move from advisory to autonomous — executing actions, accessing tools, and processing private data — fragmented monitoring is no longer enough.
The risk compounds when an agent combines privileged tool access, private data exposure, and untrusted content ingestion — what our team calls the Lethal Trifecta.
Traditional QA was built for deterministic software. Autonomous agents don't behave deterministically.
Our latest white paper lays out an integrated, 7-stage evaluation lifecycle — covering governance, runtime policy enforcement, LLM-as-a-Judge systems, and continuous feedback loops that catch drift before it becomes an incident.
https://bit.ly/4wKutWl
What if expense reporting just… handled itself? 💸
Grid Dynamics' Agent-driven Expense Management shows exactly that — an AI agent that reads receipts, matches transactions, validates details, and syncs everything directly to NetSuite. End-to-end. Conversational. Compliant.
Finance teams can cut reconciliation time in half — with full transparency and human-in-the-loop control at every step.
Less manual drudgery. More time for work that actually matters.
See the demo: https://bit.ly/3Pe9YAH
06/02/2026
Here’s how a leading healthcare RCM SaaS provider overcame a critical scalability barrier while modernizing securely in a strict PHI/HIPAA-regulated environment. https://bit.ly/49bZ4SL
Together with Grid Dynamics, the company transitioned from a tightly coupled monolith to a cloud-native microservices architecture on Microsoft Azure using the Strangler Fig pattern — enabling uninterrupted claims processing while legacy and modern services operated side by side.
The transformation established a secure, compliant, and highly scalable foundation for the company’s expanding product portfolio.
The team also introduced an AI-assisted SDLC, leveraging Grid Dynamics’ Cursor-based methodology to achieve the equivalent of nine weeks of engineering output in just three days.
The result: a future-ready claims platform with improved reliability, faster feature delivery, and substantially higher engineering productivity. https://bit.ly/49bZ4SL
05/29/2026
Corporate AI spending has surged into the hundreds of billions — yet only ~30% of enterprises are seeing measurable financial impact.
Why? Most AI initiatives optimize isolated tasks instead of the end-to-end value streams where business outcomes are actually created.
Our latest e-book explores how to make agentic AI deliver real ROI using Grid Dynamics’ enterprise transformation decision framework — helping leaders identify operational constraints, remove bottlenecks, and align AI investments with measurable business impact.
Download our e-book now: https://bit.ly/4v5FfoF
We audited search across 15 major pet retailers. The average failure rate: 34%. Broken search means lost revenue. Find out where yours stands — get your free assessment:
https://bit.ly/4wzVRpR
We tested search on 15 major pet retailers. The average failure rate? 34%.
Find out what's breaking on your site — free assessment here: https://bit.ly/4wzVRpR
05/22/2026
Writing product descriptions for a global premium denim brand used to take weeks. With AI, they cut that down to days. 👕⚡
Here's how Grid Dynamics helped them modernize product content at scale:
The problem:
Manual onboarding stretched across weeks
Multiple third parties and repeated review cycles
Hard to scale without sacrificing brand voice consistency
The solution — AI catalog enrichment:
Generative AI turns raw product data + images into ready-to-publish, on-brand descriptions
Brand style learning ensures consistent tone across the entire catalog
Automated image captioning and attribute extraction remove manual steps
A single human validation step replaces multiple review cycles
The result:
Product onboarding time: weeks → days
Merchandising teams shifted from manual content creation to brand storytelling
Faster time-to-market, at scale
If your team is still writing product descriptions manually, this case study is worth 10 minutes of your time.
📥 Download the full case study → https://bit.ly/3RnC0dE
05/21/2026
Grid Dynamics has joined forces with Ekumen, a robotics product engineering firm with 13+ years of experience delivering full-stack robotics product engineering for leading companies across the Americas, Spain, and Germany.
This acquisition deepens our Physical AI capabilities at exactly the right moment. Enterprises are moving from AI strategy to AI ex*****on, and the demand for partners who can design, build, and ship production-grade robotic systems is accelerating.
Welcome to the team, Ekumen.
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6101 Bollinger Canyon Road, Suite 465
San Ramon, CA
94583