Best ML Model Development Companies

Xebia vs Grid Dynamics: full comparison for 2026

Last updated: July 2026

Quick verdict

Xebia (4.0/5) edges ahead of Grid Dynamics (4.0/5) overall. Xebia is the better choice for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. Grid Dynamics is the stronger option for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. The right choice depends on your project size, budget, and required tech stack.

Xebia vs Grid Dynamics: head-to-head summary

Criterion Xebia Grid Dynamics
Founded 2001 2006
HQ Amsterdam, Netherlands (US HQ: Atlanta, USA) San Ramon, USA
Team size 5,001–10,000 1,001–5,000
Rating 4.0 / 5 4.0 / 5
Best for Enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery. Fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.
Pricing model Not published; enterprise project engagements Not published; enterprise custom SOWs
Min. engagement Not published Not published
Primary tech stack Python, Cloud ML platforms (AWS/Azure/GCP), MLOps tooling Microsoft Azure (AI/ML Advanced Specialization), Python, Kubernetes
Industries served Financial services, Retail, Manufacturing, Public sector Retail, Pharmaceuticals, Technology, Financial services

Xebia vs Grid Dynamics: overview

Xebia

Xebia was founded in 2001 by Rob Dielemans and Daan Teunissen in the Netherlands and has grown into a global consultancy spanning data and AI, cloud, automation, and software engineering. The Xebia Group reports between 5,000 and 10,000 employees, with corporate headquarters activity in both the Netherlands and Atlanta, Georgia. Its Data & AI Hub practice focuses on turning AI strategy into production-ready solutions, reflecting a repositioning from Xebia's original software craftsmanship and training-company roots toward an AI-first identity.

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.

Services and capabilities: Xebia vs Grid Dynamics

Capability Xebia Grid Dynamics
Custom model training
Fine-tuning & adaptation
MLOps pipeline
Model deployment & serving
Data engineering for ML
ML infrastructure management
Computer vision
NLP & LLM development
Forecasting & time-series modeling
ML strategy consulting

Tech stack comparison: Xebia vs Grid Dynamics

Framework / platform Xebia Grid Dynamics
PyTorch N/A N/A
TensorFlow N/A N/A
MLflow N/A N/A
AWS SageMaker N/A N/A
Amazon Bedrock N/A N/A
Google Cloud N/A N/A
Microsoft Azure N/A
Kubernetes
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: Xebia vs Grid Dynamics

Criterion Xebia Grid Dynamics
Minimum engagement Not published Not published
Engagement models Enterprise project engagement, Dedicated team, Training/enablement Enterprise project engagement, Managed AI services
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Xebia vs Grid Dynamics

Dimension Xebia Grid Dynamics
Best company size Enterprise Startup to mid-market
Best industries Financial services, Retail, Manufacturing Retail, Pharmaceuticals, Technology
Best use cases Turning an existing AI strategy or pilot into a production-ready, monitored system, Combining technical training/enablement with hands-on AI model development Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor, Building recommendation engines or customer intelligence models at large retail/pharma scale
Typical project type Enterprise project engagement Enterprise project engagement

Xebia vs Grid Dynamics: pros and cons

Xebia
+ 25-year software engineering and technical training pedigree underpins its AI delivery credibility.
+ Large scale (5,000–10,000 employees) supports substantial enterprise program capacity.
+ Explicit focus on production-ready AI rather than strategy-only advisory work.
+ Dual US/EU headquarters presence supports transatlantic enterprise clients.
- AI-first repositioning is relatively recent, so its dedicated AI/ML track record is shorter than its overall company history suggests.
- No clearly located aggregate Clutch/G2 star rating in available public sources.
- Pricing model and minimum engagement are not published.
- Large, multi-practice organization means AI/ML delivery quality may vary by regional team.
Grid Dynamics
+ Publicly traded status (NASDAQ: GDYN) provides audited financial transparency uncommon among private peers.
+ Reported FY2025 revenue of $411.8M with 17.5% year-over-year growth signals strong momentum.
+ Microsoft Azure Advanced Specialization certification in AI/ML.
+ Large delivery footprint (~5,000 technical professionals across 19 countries).
- Enterprise-only focus makes it a poor fit for small or mid-market buyers.
- No clearly located aggregate Clutch/G2 star rating in available public sources.
- Pricing model and minimum engagement are not published (custom SOW-based).
- Named, quantified public case studies (beyond a general pharma recommendation-engine example) are limited in available search results.

Who should choose Xebia?

Xebia is the right choice for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..

Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone.. Minimum engagement starts at Not published. Works best with clients in Financial services, Retail, Manufacturing, Public sector.

Who should choose Grid Dynamics?

Grid Dynamics is the right choice for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..

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.. Minimum engagement starts at Not published. Works best with clients in Retail, Pharmaceuticals, Technology, Financial services.

Decision matrix: Xebia vs Grid Dynamics

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Both offer fixed-price models
You need a large dedicated team for an ongoing programme Xebia
Your budget is at the lower end Compare: Xebia (Not published) vs Grid Dynamics (Not published)
You need specialist depth in a specific vertical Xebia
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build Xebia

Use case fit: Xebia vs Grid Dynamics

Use case Xebia fit Grid Dynamics fit Winner
Turning an existing AI strategy or pilot into a production-ready, monitored system Strong Limited Xebia
Combining technical training/enablement with hands-on AI model development Strong Limited Xebia
Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor Limited Strong Grid Dynamics
Building recommendation engines or customer intelligence models at large retail/pharma scale Limited Strong Grid Dynamics
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Limited Strong Grid Dynamics

Verdict: Xebia vs Grid Dynamics

Xebia (4.0/5) is the stronger overall choice for most ML Model Development projects. Quarter-century software craftsmanship and technical training heritage now applied specifically to production AI/ML delivery rather than AI strategy alone.. It is best for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery..

Grid Dynamics (4.0/5) is the better choice when fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. If your situation matches those criteria, Grid Dynamics is a competitive option.

Related comparisons

Xebia vs Grid Dynamics FAQ

Is Xebia better than Grid Dynamics?

Xebia (4.0/5) scores higher overall, but "better" depends on your use case. Xebia is better for enterprises wanting a large, engineering-craftsmanship-rooted consultancy that has repositioned around production-ready AI delivery.. Grid Dynamics is better for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..

How do Xebia and Grid Dynamics differ in pricing?

Xebia uses not published; enterprise project engagements pricing with a minimum engagement of Not published. Grid Dynamics uses not published; enterprise custom sows pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Xebia or Grid Dynamics?

Xebia is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.

What are the main differences between Xebia and Grid Dynamics?

Xebia's primary differentiator is: quarter-century software craftsmanship and technical training heritage now applied specifically to production ai/ml delivery rather than ai strategy alone.. Grid Dynamics's 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.. They also differ in team size (5,001–10,000 vs 1,001–5,000), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Retail vs Retail, Pharmaceuticals).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.