Grid Dynamics
Publicly traded (NASDAQ: GDYN) data and AI engineering company founded in 2006.
Founded 2006 | San Ramon, USA | 1,001–5,000 employees | Last updated: July 2026
mlops-pipelinecustom-model-trainingml-infrastructuredata-engineering-ml
What is Grid Dynamics?
Grid Dynamics Holdings, Inc. was founded in 2006 in Silicon Valley by Victoria Livschitz and went public via a SPAC merger with ChaSerg Technology Acquisition Corp in March 2020, trading on NASDAQ under GDYN. The company reports approximately 5,000 technical professionals delivering MLOps, generative and agentic AI, data platform engineering, recommendation engines, and computer vision work for Fortune 1000 clients, with delivery centers spanning 19 countries. Grid Dynamics holds Microsoft Azure AI/ML Advanced Specialization certification and reported FY2025 revenue of $411.8 million, up 17.5 percent year over year.
Grid Dynamics was founded in 2006 and is headquartered in San Ramon, USA. The firm employs 1,001–5,000 people and works primarily with clients in Retail, Pharmaceuticals, Technology, Financial services sectors. Its primary differentiator is: The only publicly traded company (NASDAQ: GDYN) in this comparison among the mid-to-large tier, giving buyers audited financial transparency unavailable from private peers..
Grid Dynamics tech stack and services
Microsoft Azure (AI/ML Advanced Specialization)PythonKubernetesMulti-cloud data platform tooling
| Service area | Details |
|---|---|
| Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor | Available for Retail, Pharmaceuticals, Technology, Financial services clients |
| Building recommendation engines or customer intelligence models at large retail/pharma scale | Available for Retail, Pharmaceuticals, Technology, Financial services clients |
| Running a large multi-country MLOps or generative AI implementation | Available for Retail, Pharmaceuticals, Technology, Financial services clients |
| Engaging a partner with proven Azure-certified ML infrastructure expertise | Available for Retail, Pharmaceuticals, Technology, Financial services clients |
Grid Dynamics use cases
Short answer: Grid Dynamics is best suited for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..
| Use case | Industries | Approach |
|---|---|---|
| Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor | Retail, Pharmaceuticals | Microsoft Azure (AI/ML Advanced Specialization), Python |
| Building recommendation engines or customer intelligence models at large retail/pharma scale | Retail, Pharmaceuticals | Microsoft Azure (AI/ML Advanced Specialization), Python |
| Running a large multi-country MLOps or generative AI implementation | Retail, Pharmaceuticals | Microsoft Azure (AI/ML Advanced Specialization), Python |
| Engaging a partner with proven Azure-certified ML infrastructure expertise | Retail, Pharmaceuticals | Microsoft Azure (AI/ML Advanced Specialization), Python |
Grid Dynamics pricing
Short answer: Grid Dynamics uses a not published; enterprise custom sows pricing approach. Minimum engagement starts at Not published.
| Engagement model | Typical range | Best for |
|---|---|---|
| Enterprise project engagement | Variable; depends on team size | Large programmes or team augmentation |
| Managed AI services | Variable; depends on team size | Large programmes or team augmentation |
Grid Dynamics does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Grid Dynamics pros and cons
| Advantages | Things to consider |
|---|---|
| +Publicly traded status (NASDAQ: GDYN) provides audited financial transparency uncommon among private peers. | -Enterprise-only focus makes it a poor fit for small or mid-market buyers. |
| +Reported FY2025 revenue of $411.8M with 17.5% year-over-year growth signals strong momentum. | -No clearly located aggregate Clutch/G2 star rating in available public sources. |
| +Microsoft Azure Advanced Specialization certification in AI/ML. | -Pricing model and minimum engagement are not published (custom SOW-based). |
| +Large delivery footprint (~5,000 technical professionals across 19 countries). | -Named, quantified public case studies (beyond a general pharma recommendation-engine example) are limited in available search results. |
Grid Dynamics vs alternatives
How Grid Dynamics compares to the other top ML Model Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Mid-market fintech, supply chain, and SaaS companies that... | Combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in. | 4.8 | Full comparison |
| Neurons Lab | Financial services firms wanting a boutique, engineering-led partner... | End-to-end delivery model from use-case scoping to continuous production support, with declared depth in financial services. | 4.6 | Full comparison |
| DataRoot Labs | Startups and mid-market companies wanting a senior, AI-only... | Has never diversified beyond AI/ML services, and backs its delivery bench with an in-house ML training program (DataRoot University). | 4.6 | Full comparison |
| Miquido | Companies that need ML/computer-vision capability bundled with broader... | Combines a large, review-verified product engineering practice with a dedicated AI/ML/CV specialization, useful for teams needing both app and model work from one vendor. | 4.6 | Full comparison |
| Provectus | Mid-market companies that need cloud data infrastructure and... | Grew out of cloud and big-data engineering roots, giving it particular strength in the data infrastructure layer underneath ML models, not just the models themselves. | 4.5 | Full comparison |
| Neoteric | Organizations wanting a structured feasibility/strategy phase before committing... | Two-decade operating history combined with a formal upfront feasibility-assessment stage before any model-building work begins. | 4.5 | Full comparison |
| Addepto | Cost-conscious teams that specifically need MLOps consulting or... | Dedicated MLOps-consulting service line and Clutch-reported project pricing well below several peers in this list, making it the more budget-accessible option. | 4.4 | Full comparison |
| N-iX | Enterprise buyers wanting a large, heavily certified engineering... | Broadest cloud certification footprint in this comparison (350+ across five major platforms), backed by a 200+ person dedicated data practice. | 4.4 | Full comparison |
| InData Labs | Companies needing a focused predictive-analytics or computer-vision model... | Publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims. | 4.3 | Full comparison |
| MobiDev | Small and mid-sized companies wanting a dedicated ML/data-science... | Historical Clutch #1 ranking for machine learning development (2021) combined with a specifically SME-oriented service model. | 4.3 | Full comparison |
| Sciforce | Companies needing a research-oriented boutique for NLP, digital... | R&D-first culture with named specializations in digital signal processing and NLP that are less commonly offered as distinct practice areas by peers. | 4.2 | Full comparison |
| Sigmoid | Enterprises whose primary bottleneck is data infrastructure and... | Data-engineering-first approach with 950+ multi-cloud certified engineers, positioning it as an infrastructure specialist that also delivers ML rather than the reverse. | 4.2 | Full comparison |
| Tredence | Enterprises needing vertical-specific analytics and ML applied to... | Venture-backed growth trajectory ($205M raised) with named specialization in supply chain and customer analytics rather than generic horizontal AI consulting. | 4.2 | Full comparison |
| Quantiphi | Enterprises standardized on AWS wanting a partner with... | Deepest AWS-specific partnership credentials among firms researched, including AWS GenAI Innovation Center preferred-partner status. | 4.2 | Full comparison |
| Sigma Software Group | Companies wanting a large, diversified engineering group with... | Snowflake AI Data Cloud partnership combined with unusually broad industry diversification (AdTech through aviation to gaming). | 4.1 | Full comparison |
| Intellectsoft | Companies wanting an enterprise-name client roster and a... | Unusually strong roster of large, publicly named enterprise clients (EY, Qualcomm, London Stock Exchange) for a company of its relatively modest team size. | 4.1 | Full comparison |
| ELEKS | Enterprises wanting a long-established European software engineering partner... | One of the longest operating histories (since 1991) among firms researched for this list, predating the AI consulting boom by decades. | 4.1 | Full comparison |
| Fractal Analytics | Large enterprises wanting a scaled analytics and AI... | Maintains a dedicated internal foundational AI research team alongside client delivery work, and is now a publicly listed company (NSE/BSE) rather than privately held like most peers of similar size. | 4.1 | Full comparison |
| Xebia | Enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has... | Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone. | 4.0 | Full comparison |
| Iterate.ai | Data-sensitive enterprises (e.g., regulated industries) that require AI... | Purpose-built for on-premise/private-infrastructure AI deployment, so client data and proprietary code never leave the client's own environment. | 4.0 | Full comparison |
| Modus Create | Distributed organizations wanting a remote-first partner that pairs... | Structured AI Data Foundation assessment methodology that explicitly evaluates data readiness before committing to model development. | 4.0 | Full comparison |
| Aptus Data Labs | Companies wanting a boutique, India-based data engineering and... | Combines core data engineering consulting with specific AWS AI service implementation expertise in a boutique-sized team. | 4.0 | Full comparison |
| SoftServe | Enterprises needing edge computer vision or asset-monitoring ML... | Only company in this list simultaneously holding AWS Premier, Google Cloud AI/ML Specialization, and NVIDIA Elite Consulting Partner status, reflecting particular strength in edge and GPU-accelerated computer vision. | 4.0 | Full comparison |
| DataRobot | Enterprises that want to standardize on a single... | The only platform-first vendor in this comparison, meaning model development work happens on and around DataRobot's own automated ML software rather than being platform-agnostic. | 3.9 | Full comparison |
| Persistent Systems | Mid-market and enterprise buyers wanting a publicly traded,... | Purpose-built DxH accelerator suite for MLOps and bias detection, plus a specific Everest Group Leader ranking in the mid-market Data & AI segment rather than only the largest enterprise tier. | 3.9 | Full comparison |
| EPAM Systems | Very large enterprises wanting a publicly traded, AWS... | Proprietary EPAM DIAL platform for enterprise AI orchestration, combined with the 2025 AWS Global Innovation Partner of the Year distinction, an award-level differentiator not held by most peers. | 3.9 | Full comparison |
| Globant | Large enterprises wanting industry-specific pre-packaged AI solutions ("AI... | Only company in this list organized around a formal "studio + AI Pods" delivery model, and the only one with an IDC MarketScape Worldwide Leader in AI Services designation. | 3.9 | Full comparison |
| LTIMindtree | Large enterprises, particularly in BFSI and technology/media sectors,... | Explicit ModelOps templates and model-governance/responsible-AI tooling as named, productized capabilities rather than only bespoke consulting delivery, backed by an IBM watsonx Center of Excellence. | 3.9 | Full comparison |
| Cognizant | Large enterprises, especially in healthcare, wanting a very... | Dedicated, named MLOps platform specifically built for healthcare, combined with one of the largest disclosed data/AI consultant headcounts (23,000+) in this comparison. | 3.9 | Full comparison |
| HCLTech | Very large enterprises wanting a full-stack AI vendor... | Unusually broad "chip-to-cloud" AI stack claim backed by two named proprietary platforms (Graviton for ML development, AION for AI lifecycle management), a combination not matched by most peers in this list. | 3.9 | Full comparison |
| Infosys | Very large global enterprises wanting a substantial library... | Largest disclosed library of reusable, pre-trained AI assets in this comparison (12,000+ assets, 150+ pre-trained models), positioned to accelerate delivery versus fully bespoke builds. | 3.9 | Full comparison |
| Accenture | The largest global enterprises needing AI model development... | By far the largest scale of any company in this comparison (approximately 779,000 employees, $69.67B FY2025 revenue), trading breadth and compliance maturity for less niche, hands-on model-engineering depth than boutique specialists. | 3.9 | Full comparison |
| Devbridge (a Cognizant company) | Clients who want Devbridge's original product-engineering delivery model... | The clearest ownership-change disclosure in this comparison: a formerly independent boutique now operating explicitly as a Cognizant subsidiary, combining boutique delivery heritage with large-parent-company backing. | 3.8 | Full comparison |
Grid Dynamics FAQ
What is Grid Dynamics?
Grid Dynamics Holdings, Inc. was founded in 2006 in Silicon Valley by Victoria Livschitz and went public via a SPAC merger with ChaSerg Technology Acquisition Corp in March 2020, trading on NASDAQ under GDYN. The company reports approximately 5,000 technical professionals delivering MLOps, generative and agentic AI, data platform engineering, recommendation engines, and computer vision work for Fortune 1000 clients, with delivery centers spanning 19 countries. Grid Dynamics holds Microsoft Azure AI/ML Advanced Specialization certification and reported FY2025 revenue of $411.8 million, up 17.5 percent year over year.
How much does Grid Dynamics charge?
Grid Dynamics uses not published; enterprise custom sows pricing. Minimum engagement starts at Not published. A discovery call is required to get project-specific quotes.
What tech stack does Grid Dynamics use?
Grid Dynamics works with Microsoft Azure (AI/ML Advanced Specialization), Python, Kubernetes, Multi-cloud data platform tooling. Primary industries served include Retail, Pharmaceuticals, Technology, Financial services.
Is Grid Dynamics right for enterprise?
Fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. 1,001–5,000 team size. Key consideration: Enterprise-only focus makes it a poor fit for small or mid-market buyers..
What are the best Grid Dynamics alternatives?
The best alternatives to Grid Dynamics depend on your use case. Top options are:
- Tensorway: combines classical statistical forecasting with deep learning rather than defaulting to deep learning alone, and ships with experiment tracking and monitoring built in.
- Neurons Lab: end-to-end delivery model from use-case scoping to continuous production support, with declared depth in financial services.
- DataRoot Labs: has never diversified beyond ai/ml services, and backs its delivery bench with an in-house ml training program (dataroot university).
Compare Grid Dynamics with other ML Model Development companies
Grid Dynamics vs Tensorway Grid Dynamics vs Neurons Lab Grid Dynamics vs DataRoot Labs Grid Dynamics vs Miquido Grid Dynamics vs Provectus Grid Dynamics vs Neoteric Grid Dynamics vs Addepto Grid Dynamics vs N-iX Grid Dynamics vs InData Labs Grid Dynamics vs MobiDev Grid Dynamics vs Sciforce Grid Dynamics vs Sigmoid Grid Dynamics vs Tredence Grid Dynamics vs Quantiphi Grid Dynamics vs Sigma Software Group Grid Dynamics vs Intellectsoft Grid Dynamics vs ELEKS Grid Dynamics vs Fractal Analytics Grid Dynamics vs Xebia Grid Dynamics vs Iterate.ai Grid Dynamics vs Modus Create Grid Dynamics vs Aptus Data Labs Grid Dynamics vs SoftServe Grid Dynamics vs DataRobot Grid Dynamics vs Persistent Systems Grid Dynamics vs EPAM Systems Grid Dynamics vs Globant Grid Dynamics vs LTIMindtree Grid Dynamics vs Cognizant Grid Dynamics vs HCLTech Grid Dynamics vs Infosys Grid Dynamics vs Accenture Grid Dynamics vs Devbridge (a Cognizant company)
Last reviewed: July 2026. Verify all details directly with Grid Dynamics before making a decision.