Grid Dynamics
Editor's pick #1Nasdaq-listed engineering firm where AI work passed 30% of revenue in 2026
What is Grid Dynamics?
Grid Dynamics was founded in 2006, is headquartered in San Ramon, California, and has more than 4,000 employees, mostly engineers. Since listing on Nasdaq it reports results quarterly, and in the second quarter of 2026 AI-related revenue reached 30.7% of the total, which management attributed to client projects moving from pilots into production. Its GAIN platforms package repeatable work for agentic commerce, software delivery, risk and compliance, and physical AI, and forward-deployed engineers adapt them to each client. Management also said on the same call that clients worry about token costs, so expect cost questions to come up early.
Grid Dynamics works primarily with clients in Retail & e-commerce, Financial services, Manufacturing, Media, Technology sectors. Its primary differentiator is: Forward-deployed engineers working from ready-made GAIN platforms for agentic and retail AI.
Grid Dynamics tech stack and services
| Service area |
|---|
| Pilot to Production |
| Agentic AI |
| MLOps & Model Serving |
| Data Engineering |
| Google Cloud Partner |
| AWS Partner |
Grid Dynamics pricing
Short answer: Grid Dynamics prices its work as follows: time & materials and dedicated teams; rates not published. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Time & materials | Hourly; see pricing model above | Scope that will change as you learn |
| Dedicated team | Monthly team rate; not public | Continuing the build after a pilot |
Grid Dynamics pros and cons
| Advantages | Things to consider |
|---|---|
| +AI is now close to a third of revenue, so production AI is a main line of business | -Rates and minimums are not published |
| +Ready-made GAIN platforms shorten the path for retail and agentic use cases | -Better suited to large programs than a single small pilot |
| +Large engineering bench in Eastern Europe, Latin America, and India | -Platform-based delivery can steer designs toward its own GAIN components |
| +Public company with quarterly disclosures |
Grid Dynamics vs alternatives
How Grid Dynamics compares to the other top AI Implementation providers.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Teams whose AI pilot works but can't ship. | Model gateway with routing, provider fallback, and regression tests, released through a canary rollout | 4.8 | Full comparison |
| Provectus | AWS shops taking GenAI pilots to production. | AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker | 4.6 | Full comparison |
| deepsense.ai | Teams that need measured accuracy before launch. | Evaluation-first engineering that proves accuracy on your data before release | 4.5 | Full comparison |
| Neurons Lab | Banks and insurers shipping AI on AWS. | Financial-services AI built inside existing compliance controls on AWS | 4.4 | Full comparison |
| Datatonic | Google Cloud users needing MLOps and managed run. | Vertex AI MLOps with a managed service to run models after launch | 4.4 | Full comparison |
| Quantiphi | Large document and contact-center AI programs. | Large Google Cloud and AWS engineering bench for document and speech AI in production | 4.3 | Full comparison |
| ML6 | European firms needing EU-compliant production AI. | European AI engineering with EU AI Act and GDPR requirements built into delivery | 4.3 | Full comparison |
| Thoughtworks | Engineering orgs wanting disciplined AI delivery. | Continuous delivery practice applied to models and prompts, with tool views published in its Technology Radar | 4.3 | Full comparison |
| N-iX | Mid-size and large firms wanting nearshore MLOps. | Dedicated MLOps practice backed by a large nearshore engineering bench | 4.2 | Full comparison |
| DS Stream | Teams wanting packaged LLMOps at nearshore rates. | Packaged LLMOps setup with evaluation, prompt versioning, guardrails, and model routing | 4.2 | Full comparison |
| Addepto | Mid-size firms wanting tested LLM apps cheaply. | Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point | 4.2 | Full comparison |
| RTS Labs | US mid-market firms on a small budget. | The lowest entry point on this page, with a committed ship date for production code | 4.1 | Full comparison |
| EPAM Systems | Enterprises adding AI across many products. | Engineering capacity to put AI into dozens of products under one program | 4.1 | Full comparison |
| Accenture | Multinationals rolling AI out across many countries. | Staffing and compliance depth to run production AI in many countries at once | 4.1 | Full comparison |
| Winder.ai | Teams needing senior MLOps advice and review. | Senior MLOps expertise from a recognized author, at boutique scale | 4.0 | Full comparison |
| NineTwoThree AI Studio | Funded companies launching an AI product. | Product design and engineering together for customer-facing AI launches | 4.0 | Full comparison |
| Globant | US firms wanting nearshore AI engineering. | Nearshore Latin American engineering teams in US time zones | 4.0 | Full comparison |
| SoftServe | Existing clients extending engineering into AI. | Google Cloud Premier engineering firm with an MLOps and generative AI practice | 4.0 | Full comparison |
| Capgemini | European multinationals pairing AI with outsourcing. | Production AI bundled with outsourced business operations after the WNS deal | 3.9 | Full comparison |
| InData Labs | Mid-size firms with one focused AI project. | Discovery, proof of concept, and production build from a small data science team | 3.9 | Full comparison |
| Instinctools | Palantir users building agentic workflows. | Palantir Foundry and AIP implementation alongside custom software engineering | 3.9 | Full comparison |
| Netguru | Product teams adding AI features to apps. | AI features shipped as part of web and mobile product work | 3.9 | Full comparison |
| STX Next | Python teams needing extra AI engineers. | Python engineering depth for AI that lives inside your codebase | 3.9 | Full comparison |
| 10Clouds | Smaller banks and lenders adding AI. | A dedicated financial-institutions AI unit with its own AIConsole platform | 3.8 | Full comparison |
| LeewayHertz | Buyers wanting a platform-based AI build. | Builds on its own ZBrain platform, now backed by The Hackett Group | 3.7 | Full comparison |
Grid Dynamics FAQ
What is Grid Dynamics?
Nasdaq-listed engineering firm where AI work passed 30% of revenue in 2026
How much does Grid Dynamics charge?
Pricing model: time & materials and dedicated teams; rates not published. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does Grid Dynamics use?
Grid Dynamics works with Google Cloud, AWS, Azure, Kubernetes, Databricks. Primary industries served include Retail & e-commerce, Financial services, Manufacturing, Media, Technology.
Is Grid Dynamics right for enterprise?
Best for: enterprises moving several AI pilots to production. Team size: 4,000+. Key consideration: Rates and minimums are not published.
What are the best Grid Dynamics alternatives?
The best alternatives to Grid Dynamics depend on your use case. Top options are:
- Tensorway: model gateway with routing, provider fallback, and regression tests, released through a canary rollout
- Provectus: AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker
- deepsense.ai: evaluation-first engineering that proves accuracy on your data before release
Compare Grid Dynamics with other AI Implementation providers
Verify all details directly with Grid Dynamics before making a decision.