ELEKS vs Modak: full comparison for 2026
Last updated: July 2026
Quick verdict
ELEKS (3.9/5) edges ahead of Modak (3.7/5) overall. ELEKS is the better choice for enterprise clients needing ML within a full-service technology consulting engagement with long-term continuity. 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.
ELEKS vs Modak: head-to-head summary
| Criterion | ELEKS | Modak |
|---|---|---|
| Founded | 1991 | 2016 |
| HQ | Lviv, Ukraine | San Jose, CA |
| Team size | 2,000+ | 100–200 |
| Rating | 3.9 / 5 | 3.7 / 5 |
| Best for | Enterprise clients needing ML within a full-service technology consulting engagement with long-term continuity | Large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption |
| Pricing model | T&M, dedicated team | T&M, retainer |
| Min. engagement | $50K+ | $50K+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Apache Spark, Databricks |
| Industries served | financial, healthcare, manufacturing, retail, logistics | financial, healthcare, manufacturing, logistics, saas |
ELEKS vs Modak: overview
ELEKS
ELEKS was established in 1991 and is headquartered in Lviv, Ukraine, with offices across Europe and North America. The company has 2,000+ engineers and delivers technology consulting, AI/ML services, and enterprise software for Fortune 500 clients globally. ML services include predictive analytics, computer vision, NLP, and intelligent automation. ELEKS celebrated its 30th anniversary in 2021. (Founding year and team size per ELEKS official website and KyivPost article.)
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: ELEKS vs Modak
| Capability | ELEKS | 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: ELEKS vs Modak
| Framework / platform | ELEKS | Modak |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| PyTorch | ✓ | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: ELEKS vs Modak
| Criterion | ELEKS | Modak |
|---|---|---|
| Minimum engagement | $50K+ | $50K+ |
| Engagement models | T&M, Dedicated team | T&M, Retainer |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: ELEKS vs Modak
| Dimension | ELEKS | Modak |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | financial, healthcare, manufacturing | financial, healthcare, manufacturing |
| Best use cases | ML integration into enterprise ERP or CRM, Computer vision for manufacturing quality control | Enterprise data modernisation for AI readiness, ML-powered ETL and data prep pipeline |
| Typical project type | T&M | T&M |
ELEKS vs Modak: pros and cons
| ELEKS | |
|---|---|
| + | 30+ years of enterprise delivery history — very low company risk |
| + | 2,000+ engineers across multiple disciplines |
| + | Proven Fortune 500 delivery capability across multiple verticals |
| + | Wide industry coverage including manufacturing and financial services |
| - | ML practice is secondary to broader software engineering — not ML-first |
| - | Ukraine-based delivery carries geographic risk considerations for some clients |
| - | Less agile than boutique ML specialists for short exploratory projects |
| 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 ELEKS?
ELEKS is the right choice for enterprise clients needing ML within a full-service technology consulting engagement with long-term continuity.
30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, manufacturing, retail, 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: ELEKS vs Modak
| 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 | ELEKS |
| Your budget is at the lower end | ELEKS |
| You need specialist depth in a specific vertical | ELEKS |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | ELEKS |
Use case fit: ELEKS vs Modak
| Use case | ELEKS fit | Modak fit | Winner |
|---|---|---|---|
| ML integration into enterprise ERP or CRM | Strong | Strong | Both equally |
| Computer vision for manufacturing quality control | Strong | Limited | ELEKS |
| Enterprise data modernisation for AI readiness | Strong | Strong | Both equally |
| ML-powered ETL and data prep pipeline | Limited | Strong | Modak |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: ELEKS vs Modak
ELEKS (3.9/5) is the stronger overall choice for most Machine Learning projects. 30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers. It is best for enterprise clients needing ML within a full-service technology consulting engagement with long-term continuity.
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.
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ELEKS vs Modak FAQ
Is ELEKS better than Modak?
ELEKS (3.9/5) scores higher overall, but "better" depends on your use case. ELEKS is better for enterprise clients needing ML within a full-service technology consulting engagement with long-term continuity. Modak is better for large enterprises needing AI-driven data modernisation to prepare unstructured data for ML consumption.
How do ELEKS and Modak differ in pricing?
ELEKS uses t&m, dedicated team pricing with a minimum engagement of $50K+. 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: ELEKS 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 ELEKS and Modak?
ELEKS's primary differentiator is: 30+ years of enterprise software delivery — ml within a stable, large-org structure for risk-averse buyers. 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 (2,000+ vs 100–200), minimum engagement ($50K+ vs $50K+), and primary industries served (financial, healthcare vs financial, healthcare).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.