Best Machine Learning Agencies

DATAFOREST vs Modak: full comparison for 2026

Last updated: July 2026

Quick verdict

DATAFOREST (4.0/5) edges ahead of Modak (3.7/5) overall. DATAFOREST is the better choice for uS and EU companies seeking competitively priced custom AI and data engineering with verified Clutch ratings. Modak is the stronger option for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption. The right choice depends on your project size, budget, and required tech stack.

DATAFOREST vs Modak: head-to-head summary

Criterion DATAFOREST Modak
Founded 2017 2016
HQ Kyiv, Ukraine San Jose, CA
Team size 50–100 100–200
Rating 4.0 / 5 3.7 / 5
Best for US and EU companies seeking competitively priced custom AI and data engineering with verified Clutch ratings Large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption
Pricing model Fixed project, T&M T&M, retainer
Min. engagement $8K+ $50K+
Primary tech stack Python, Apache Spark, AWS Python, Apache Spark, Databricks
Industries served saas, fintech, retail, healthcare, logistics financial, healthcare, manufacturing, logistics, saas

DATAFOREST vs Modak: overview

DATAFOREST

DATAFOREST was founded in 2017 and is headquartered in Kyiv, Ukraine. The company specialises in custom AI software development, data engineering, and data lake architecture, with projects ranging from $8,000 to $460,000 (per Clutch profile data). DATAFOREST holds a 4.9-star Clutch rating across 27 verified reviews and an A+ DesignRush rating, with clients primarily in the US and EU. Services include ETL pipelines, data lake build-outs, predictive analytics, and ML model development. (Project range and ratings from Clutch and DesignRush verified profiles.)

Modak

Modak is an AI-native data engineering company headquartered in San Jose, California, founded in 2016. The company uses machine learning techniques to transform how structured and unstructured enterprise data is prepared, consumed, and shared — focusing on AI-driven data modernisation for large organisations. Global consulting services help enterprises modernise data infrastructure, accelerate AI readiness, and drive measurable business outcomes. (Founding year and approach per Modak official website and ZoomInfo.)

Services and capabilities: DATAFOREST vs Modak

Capability DATAFOREST Modak
Custom ML build
ML consulting
Computer vision
NLP / LLM
Predictive analytics
MLOps
Data engineering
Generative AI
Staff augmentation
Fixed-price projects
Dedicated team model

Tech stack comparison: DATAFOREST vs Modak

Framework / platform DATAFOREST Modak
Python
TensorFlow N/A N/A
PyTorch N/A N/A
AWS SageMaker N/A N/A
Azure ML N/A N/A

Pricing comparison: DATAFOREST vs Modak

Criterion DATAFOREST Modak
Minimum engagement $8K+ $50K+
Engagement models Fixed project, T&M T&M, Retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: DATAFOREST vs Modak

Dimension DATAFOREST Modak
Best company size Startup to mid-market Startup to mid-market
Best industries saas, fintech, retail financial, healthcare, manufacturing
Best use cases Data lake architecture and build-out, ETL pipeline for analytics platform Enterprise data modernisation for AI readiness, ML-powered ETL and data prep pipeline
Typical project type Fixed project T&M

DATAFOREST vs Modak: pros and cons

DATAFOREST
+ 4.9-star Clutch rating across 27 verified client reviews
+ Projects start from $8K — one of the most accessible entry points in the category
+ Strong data engineering: data lakes, ETL pipelines, Airflow orchestration
+ Transparent project scoping and pricing
+ A+ DesignRush rating
- Smaller team limits very large concurrent programmes
- Ukraine-based delivery carries geographic risk considerations for some clients
Modak
+ ML applied to data engineering itself — accelerates data prep for ML programmes
+ AI-native from inception — not a repositioned data warehouse firm
+ Strong on unstructured data processing for AI readiness
+ San Jose HQ with enterprise client focus
- Data engineering focus — not suited to custom ML model development or computer vision
- Minimum engagement oriented toward large enterprise programmes
- Less suited to companies without an existing large data estate

Who should choose DATAFOREST?

DATAFOREST is the right choice for uS and EU companies seeking competitively priced custom AI and data engineering with verified Clutch ratings.

4.9-star Clutch rating across 27 verified reviews — one of the highest-rated AI firms in Eastern Europe. Minimum engagement starts at $8K+. Works best with clients in saas, fintech, retail, healthcare, logistics.

Who should choose Modak?

Modak is the right choice for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.

ML-powered data engineering — uses ML itself to accelerate data prep and modernisation at enterprise scale. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, manufacturing, logistics, saas.

Decision matrix: DATAFOREST vs Modak

Your situation Recommended choice
You need full-ownership delivery on a defined project scope DATAFOREST
You need a large dedicated team for an ongoing programme Check each company's engagement model
Your budget is at the lower end DATAFOREST
You need specialist depth in a specific vertical DATAFOREST
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build DATAFOREST

Use case fit: DATAFOREST vs Modak

Use case DATAFOREST fit Modak fit Winner
Data lake architecture and build-out Strong Strong Both equally
ETL pipeline for analytics platform Strong Strong Both equally
Enterprise data modernisation for AI readiness Limited Strong Modak
ML-powered ETL and data prep pipeline Limited Strong Modak
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: DATAFOREST vs Modak

DATAFOREST (4.0/5) is the stronger overall choice for most Machine Learning projects. 4.9-star Clutch rating across 27 verified reviews — one of the highest-rated AI firms in Eastern Europe. It is best for uS and EU companies seeking competitively priced custom AI and data engineering with verified Clutch ratings.

Modak (3.7/5) is the better choice when large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption. If your situation matches those criteria, Modak is a competitive option.

Related comparisons

DATAFOREST vs Modak FAQ

Is DATAFOREST better than Modak?

DATAFOREST (4.0/5) scores higher overall, but "better" depends on your use case. DATAFOREST is better for uS and EU companies seeking competitively priced custom AI and data engineering with verified Clutch ratings. Modak is better for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.

How do DATAFOREST and Modak differ in pricing?

DATAFOREST uses fixed project, t&m pricing with a minimum engagement of $8K+. Modak uses t&m, retainer pricing with a minimum engagement of $50K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: DATAFOREST or Modak?

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

What are the main differences between DATAFOREST and Modak?

DATAFOREST's primary differentiator is: 4.9-star clutch rating across 27 verified reviews — one of the highest-rated ai firms in eastern europe. Modak's primary differentiator is: ml-powered data engineering — uses ml itself to accelerate data prep and modernisation at enterprise scale. They also differ in team size (50–100 vs 100–200), minimum engagement ($8K+ vs $50K+), and primary industries served (saas, fintech vs financial, healthcare).

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