Best ML Model Development Companies

Grid Dynamics vs Modus Create: full comparison for 2026

Last updated: July 2026

Quick verdict

Grid Dynamics (4.0/5) edges ahead of Modus Create (4.0/5) overall. Grid Dynamics is the better choice for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. Modus Create is the stronger option for distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery.. The right choice depends on your project size, budget, and required tech stack.

Grid Dynamics vs Modus Create: head-to-head summary

Criterion Grid Dynamics Modus Create
Founded 2006 2011
HQ San Ramon, USA Reston, USA
Team size 1,001–5,000 501–1,000
Rating 4.0 / 5 4.0 / 5
Best for Fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner. Distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery.
Pricing model Not published; enterprise custom SOWs Not published; project and dedicated team
Min. engagement Not published Not published
Primary tech stack Microsoft Azure (AI/ML Advanced Specialization), Python, Kubernetes Python, AWS, Data governance tooling
Industries served Retail, Pharmaceuticals, Technology, Financial services Technology/SaaS, Retail, Healthcare

Grid Dynamics vs Modus Create: overview

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.

Modus Create

Modus Create is a fully remote, distributed product engineering company founded in 2011 and headquartered in Reston, Virginia, with team members spread across more than 55 countries. The company's AI/ML and data engineering practice includes AI Strategy Roadmap assessments and AI Data Foundation assessments intended to ensure underlying data is reliable and properly governed before or alongside model development work. Modus Create has partnered with technology providers including Atlassian, GitHub, and AWS, and has been recognized on the Inc. 5000 list for nine consecutive years.

Services and capabilities: Grid Dynamics vs Modus Create

Capability Grid Dynamics Modus Create
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: Grid Dynamics vs Modus Create

Framework / platform Grid Dynamics Modus Create
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 N/A
Snowflake N/A N/A
NVIDIA N/A N/A

Pricing comparison: Grid Dynamics vs Modus Create

Criterion Grid Dynamics Modus Create
Minimum engagement Not published Not published
Engagement models Enterprise project engagement, Managed AI services Fixed project, Dedicated team, Assessment/audit engagement
Rate transparency Not public Not public
Price tier Mid-market Mid-market

Target audience comparison: Grid Dynamics vs Modus Create

Dimension Grid Dynamics Modus Create
Best company size Startup to mid-market Mid-market to enterprise
Best industries Retail, Pharmaceuticals, Technology Technology/SaaS, Retail, Healthcare
Best use cases Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor, Building recommendation engines or customer intelligence models at large retail/pharma scale Running an AI Data Foundation assessment before committing to a full model-development engagement, Building an AI strategy roadmap for an organization new to machine learning adoption
Typical project type Enterprise project engagement Fixed project

Grid Dynamics vs Modus Create: pros and cons

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.
Modus Create
+ Structured AI Data Foundation assessment reduces risk of building models on ungoverned or unreliable data.
+ Fully remote, globally distributed team (55+ countries) offers broad timezone coverage.
+ Nine consecutive years on the Inc. 5000 list signals sustained growth.
+ Technology partnerships with Atlassian, GitHub, and AWS support integrated delivery tooling.
- AI/ML is one of several product engineering service lines rather than the company's sole specialization.
- No clearly located aggregate Clutch/G2 star rating in available public sources.
- Pricing model and minimum engagement are not published.
- Fully remote delivery model may not suit buyers who prefer localized or on-site teams.

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.

Who should choose Modus Create?

Modus Create is the right choice for distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery..

Structured AI Data Foundation assessment methodology that explicitly evaluates data readiness before committing to model development.. Minimum engagement starts at Not published. Works best with clients in Technology/SaaS, Retail, Healthcare.

Decision matrix: Grid Dynamics vs Modus Create

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

Use case fit: Grid Dynamics vs Modus Create

Use case Grid Dynamics fit Modus Create fit Winner
Fortune 1000 companies needing an audited, publicly accountable ML engineering vendor Strong Limited Grid Dynamics
Building recommendation engines or customer intelligence models at large retail/pharma scale Strong Strong Both equally
Running an AI Data Foundation assessment before committing to a full model-development engagement Strong Strong Both equally
Building an AI strategy roadmap for an organization new to machine learning adoption Strong Strong Both equally
Fixed-price build Limited Limited Both equally
MLOps pipeline setup Strong Limited Grid Dynamics

Verdict: Grid Dynamics vs Modus Create

Grid Dynamics (4.0/5) is the stronger overall choice for most ML Model Development projects. 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.. It is best for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner..

Modus Create (4.0/5) is the better choice when distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery.. If your situation matches those criteria, Modus Create is a competitive option.

Related comparisons

Grid Dynamics vs Modus Create FAQ

Is Grid Dynamics better than Modus Create?

Grid Dynamics (4.0/5) scores higher overall, but "better" depends on your use case. Grid Dynamics is better for fortune 1000 companies wanting the financial transparency and scale of a publicly traded ML engineering partner.. Modus Create is better for distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery..

How do Grid Dynamics and Modus Create differ in pricing?

Grid Dynamics uses not published; enterprise custom sows pricing with a minimum engagement of Not published. Modus Create uses not published; project and dedicated team 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: Grid Dynamics or Modus Create?

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 Modus Create?

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.. Modus Create's primary differentiator is: structured ai data foundation assessment methodology that explicitly evaluates data readiness before committing to model development.. They also differ in team size (1,001–5,000 vs 501–1,000), minimum engagement (Not published vs Not published), and primary industries served (Retail, Pharmaceuticals vs Technology/SaaS, Retail).

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