Best ML Development Services

Grid Dynamics vs Yalantis: full comparison for 2026

Last updated: July 2026

Quick verdict

Grid Dynamics (4.4/5) edges ahead of Yalantis (4.0/5) overall. Grid Dynamics is the better choice for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs.. Yalantis is the stronger option for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. The right choice depends on your project size, budget, and required tech stack.

Grid Dynamics vs Yalantis: head-to-head summary

Criterion Grid Dynamics Yalantis
Founded 2006 2008
HQ San Ramon, California, United States Larnaca, Cyprus
Team size 4,500+ 500+
Rating 4.4 / 5 4.0 / 5
Best for Fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs. Compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.
Pricing model Time & materials, managed engagement Fixed project, dedicated team
Min. engagement Not published $10,000
Primary tech stack AWS SageMaker, Kubernetes, Apache Spark AWS SageMaker, Azure ML, Google Cloud Vertex AI
Industries served Retail & E-commerce, Manufacturing, Insurance, Media & Entertainment, Telecom Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain

Grid Dynamics vs Yalantis: overview

Grid Dynamics

Grid Dynamics Holdings, Inc. (Nasdaq: GDYN) was founded in 2006 in Silicon Valley by Leonard Livschitz and is headquartered in San Ramon, California, with roughly 4,500–5,000 technical professionals across 19 countries. The company delivers enterprise AI/ML and data platform engineering alongside cloud-native engineering, serving Fortune 1000 clients in retail, manufacturing, insurance, wealth management, and life sciences. As a publicly traded company, Grid Dynamics carries a higher compliance and financial-transparency bar than most privately held firms in this list, at the cost of boutique-level personalization.

Yalantis

Yalantis was founded in 2008 with headquarters in Larnaca, Cyprus and development hubs in Dnipro, Kyiv, and Lviv, Ukraine, growing to roughly 500 specialists. The firm positions itself as a 'compliance-first engineering partner,' building high-performance ML models across Amazon, Microsoft Azure, and Google Cloud ML platforms, including data preparation, model selection, training, deployment, and multimodal LLM processing for visual and text data. Project costs are reported to range from $10,000 to over $800,000, indicating the firm handles both small scoped projects and large enterprise programs.

Services and capabilities: Grid Dynamics vs Yalantis

Capability Grid Dynamics Yalantis
Custom ML Models
Computer Vision
NLP
MLOps
Generative AI
AI Consulting

Tech stack comparison: Grid Dynamics vs Yalantis

Framework / platform Grid Dynamics Yalantis
TensorFlow N/A
PyTorch N/A
AWS
Azure N/A
Google Cloud N/A
LangChain N/A
Hugging Face N/A N/A
Kubernetes N/A

Pricing comparison: Grid Dynamics vs Yalantis

Criterion Grid Dynamics Yalantis
Minimum engagement Not published $10,000
Engagement models Dedicated team, Managed engagement, Staff augmentation Fixed project, Dedicated team, Staff augmentation
Rate transparency Not public Minimum disclosed
Price tier Mid-market Accessible

Target audience comparison: Grid Dynamics vs Yalantis

Dimension Grid Dynamics Yalantis
Best company size Startup to mid-market Startup to mid-market
Best industries Retail & E-commerce, Manufacturing, Insurance Healthcare, IoT & Embedded Systems, FinTech
Best use cases Fortune 1000 retailer needs an enterprise-scale ML/data platform overhaul with public-company accountability., Insurance or wealth management firm needs a vendor with SEC-level financial transparency for procurement due diligence. Healthcare or IoT company needs ML development from a compliance-first engineering partner., Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform.
Typical project type Dedicated team Fixed project

Grid Dynamics vs Yalantis: pros and cons

Grid Dynamics
+ Publicly traded (Nasdaq: GDYN) status means audited financials and SEC disclosure are available to prospective clients — a rare transparency level in this list.
+ ~4,500 technical professionals across 19 countries gives it the delivery capacity for large, multi-workstream Fortune 1000 programs.
+ 18 years of enterprise engineering experience since 2006, well before the current AI hiring wave.
+ Combines cloud-native and AI/ML engineering under one roof, reducing multi-vendor coordination for large programs.
- At ~4,500 employees, engagements are structured around managed delivery teams rather than boutique-style founder involvement.
- Public-company overhead and scale generally mean higher minimum program sizes than smaller specialist firms.
Yalantis
+ Compliance-first positioning is a genuine differentiator for regulated industries like healthcare and embedded/IoT systems.
+ Multi-cloud ML delivery capability (AWS, Azure, GCP) avoids vendor lock-in to a single hyperscaler.
+ Wide project-cost range ($10,000–$800,000+) means the firm can serve both small scoped projects and large programs without switching vendors.
+ 500+ specialists across three Ukrainian development hubs provides meaningful delivery redundancy.
- IoT and hardware engineering heritage means ML is one of several engineering disciplines rather than the firm's sole focus.
- Larnaca, Cyprus legal HQ with all technical delivery in Ukraine is standard for the region but worth confirming for contract jurisdiction purposes.

Who should choose Grid Dynamics?

Grid Dynamics is the right choice for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs..

Nasdaq-listed enterprise AI engineering firm with public financial reporting and Fortune 1000 client base.. Minimum engagement starts at Not published. Works best with clients in Retail & E-commerce, Manufacturing, Insurance, Media & Entertainment, Telecom.

Who should choose Yalantis?

Yalantis is the right choice for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..

Compliance-first positioning combined with multi-cloud ML delivery (AWS, Azure, GCP) under one roof.. Minimum engagement starts at $10,000. Works best with clients in Healthcare, IoT & Embedded Systems, FinTech, Logistics & Supply Chain.

Decision matrix: Grid Dynamics vs Yalantis

Your situation Recommended choice
You need full-ownership delivery on a defined project scope Yalantis
You need a large dedicated team for an ongoing programme Grid Dynamics
Your budget is at the lower end Compare: Grid Dynamics (Not published) vs Yalantis ($10,000)
You need specialist depth in a specific vertical Grid Dynamics
You need production MLOps support after model launch Both offer MLOps support
You need consulting before committing to a build Both may offer discovery engagements

Use case fit: Grid Dynamics vs Yalantis

Use case Grid Dynamics fit Yalantis fit Winner
Fortune 1000 retailer needs an enterprise-scale ML/data platform overhaul with public-company accountability. Strong Limited Grid Dynamics
Insurance or wealth management firm needs a vendor with SEC-level financial transparency for procurement due diligence. Strong Limited Grid Dynamics
Healthcare or IoT company needs ML development from a compliance-first engineering partner. Limited Strong Yalantis
Company wants flexibility to deploy models across AWS, Azure, or GCP without being locked into one platform. Strong Strong Both equally
Fixed-scope ML build Limited Limited Both equally
Ongoing model retraining Limited Limited Both equally

Verdict: Grid Dynamics vs Yalantis

Grid Dynamics (4.4/5) is the stronger overall choice for most Machine Learning Development projects. Nasdaq-listed enterprise AI engineering firm with public financial reporting and Fortune 1000 client base.. It is best for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs..

Yalantis (4.0/5) is the better choice when compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms.. If your situation matches those criteria, Yalantis is a competitive option.

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Grid Dynamics vs Yalantis FAQ

Is Grid Dynamics better than Yalantis?

Grid Dynamics (4.4/5) scores higher overall, but "better" depends on your use case. Grid Dynamics is better for fortune 1000 enterprises that need public-company financial transparency and large-scale delivery capacity for ML/AI programs.. Yalantis is better for compliance-sensitive industries (IoT, healthcare, embedded systems) that need ML delivery across all three major cloud platforms..

How do Grid Dynamics and Yalantis differ in pricing?

Grid Dynamics uses time & materials, managed engagement pricing with a minimum engagement of Not published. Yalantis uses fixed project, dedicated team pricing with a minimum engagement of $10,000. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Grid Dynamics or Yalantis?

Grid Dynamics 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 Grid Dynamics and Yalantis?

Grid Dynamics's primary differentiator is: nasdaq-listed enterprise ai engineering firm with public financial reporting and fortune 1000 client base.. Yalantis's primary differentiator is: compliance-first positioning combined with multi-cloud ml delivery (aws, azure, gcp) under one roof.. They also differ in team size (4,500+ vs 500+), minimum engagement (Not published vs $10,000), and primary industries served (Retail & E-commerce, Manufacturing vs Healthcare, IoT & Embedded Systems).

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