Best Machine Learning Agencies

DataArt vs Avenga: full comparison for 2026

Last updated: July 2026

Quick verdict

DataArt (3.9/5) edges ahead of Avenga (3.9/5) overall. DataArt is the better choice for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. Avenga is the stronger option for european enterprise clients seeking large-scale ML and digital transformation from a well-resourced regional firm. The right choice depends on your project size, budget, and required tech stack.

DataArt vs Avenga: head-to-head summary

Criterion DataArt Avenga
Founded 1997 2019
HQ New York, NY Prague, Czech Republic
Team size 5,700+ 3,884
Rating 3.9 / 5 3.9 / 5
Best for Enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth European enterprise clients seeking large-scale ML and digital transformation from a well-resourced regional firm
Pricing model T&M, dedicated team T&M, dedicated team
Min. engagement $50K+ $50K+
Primary tech stack Python, TensorFlow, PyTorch Python, Azure, AWS
Industries served fintech, healthcare, travel, media, retail financial, healthcare, retail, telecommunications, manufacturing

DataArt vs Avenga: overview

DataArt

DataArt was founded in 1997 by Eugene Goland and is headquartered in New York, with offices across 15 global locations and 5,700+ employees. The company delivers AI and ML services — predictive analytics, NLP, data mining, and computer vision — alongside broader software engineering for clients in fintech, healthcare, and travel. DataArt was named an Inc. 5000 honoree in 2024. ML is one service line among many in DataArt's broad software engineering portfolio. (Employee count and founding year per DataArt Wikipedia and official website.)

Avenga

Avenga was formed in 2019 through the merger of multiple European IT firms and is headquartered in Prague, Czech Republic, with approximately 3,884 employees as of December 2025 (per Avenga LinkedIn). The company provides AI, ML, and digital transformation services for enterprise clients, drawing on its merged entities' combined delivery capabilities across finance, healthcare, and retail. (Employee count per Avenga LinkedIn, December 2025; merger history per Avenga Wikipedia.)

Services and capabilities: DataArt vs Avenga

Capability DataArt Avenga
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: DataArt vs Avenga

Framework / platform DataArt Avenga
Python
TensorFlow
PyTorch N/A
AWS SageMaker N/A N/A
Azure ML N/A N/A

Pricing comparison: DataArt vs Avenga

Criterion DataArt Avenga
Minimum engagement $50K+ $50K+
Engagement models T&M, Dedicated team, Retainer T&M, Dedicated team
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: DataArt vs Avenga

Dimension DataArt Avenga
Best company size Startup to mid-market Startup to mid-market
Best industries fintech, healthcare, travel financial, healthcare, retail
Best use cases ML feature integration into existing fintech platform, Travel recommendation engine Enterprise ML platform within digital transformation programme, Data modernisation with ML integration for financial services
Typical project type T&M T&M

DataArt vs Avenga: pros and cons

DataArt
+ 5,700+ engineers — sufficient capacity for large parallel programmes
+ 29 years of software delivery history — low company risk
+ Strong fintech and travel sector domain depth
+ Inc. 5000 2024 — verified revenue growth
+ 15 global offices for enterprise procurement alignment
- ML is one practice among many — not a pure ML specialist
- Minimum engagement and overhead suited to enterprise, not startups
- Large firm processes can reduce speed relative to boutique ML agencies
Avenga
+ 3,800+ engineers — strong capacity for large-scale programmes
+ European delivery presence across multiple countries
+ Multi-sector ML experience: finance, healthcare, retail, telecom
- Formed from merger in 2019 — company culture and process integration still maturing
- ML is part of broader IT consulting — not ML-first
- Large minimum engagements not suited to startups or SMBs

Who should choose DataArt?

DataArt is the right choice for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth.

1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ML and software in fintech and travel. Minimum engagement starts at $50K+. Works best with clients in fintech, healthcare, travel, media, retail.

Who should choose Avenga?

Avenga is the right choice for european enterprise clients seeking large-scale ML and digital transformation from a well-resourced regional firm.

Formed from a 2019 merger — 3,800+ engineers across Europe for large ML and digital transformation programmes. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, retail, telecommunications, manufacturing.

Decision matrix: DataArt vs Avenga

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 DataArt
Your budget is at the lower end DataArt
You need specialist depth in a specific vertical DataArt
You need staff augmentation or team extension Neither; consider alternatives that offer staff aug
You need consulting before committing to a build DataArt

Use case fit: DataArt vs Avenga

Use case DataArt fit Avenga fit Winner
ML feature integration into existing fintech platform Strong Strong Both equally
Travel recommendation engine Strong Limited DataArt
Enterprise ML platform within digital transformation programme Strong Strong Both equally
Data modernisation with ML integration for financial services Strong Strong Both equally
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: DataArt vs Avenga

DataArt (3.9/5) is the stronger overall choice for most Machine Learning projects. 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ML and software in fintech and travel. It is best for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth.

Avenga (3.9/5) is the better choice when european enterprise clients seeking large-scale ML and digital transformation from a well-resourced regional firm. If your situation matches those criteria, Avenga is a competitive option.

Related comparisons

DataArt vs Avenga FAQ

Is DataArt better than Avenga?

DataArt (3.9/5) scores higher overall, but "better" depends on your use case. DataArt is better for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. Avenga is better for european enterprise clients seeking large-scale ML and digital transformation from a well-resourced regional firm.

How do DataArt and Avenga differ in pricing?

DataArt uses t&m, dedicated team pricing with a minimum engagement of $50K+. Avenga uses t&m, dedicated team 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: DataArt or Avenga?

DataArt 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 DataArt and Avenga?

DataArt's primary differentiator is: 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ml and software in fintech and travel. Avenga's primary differentiator is: formed from a 2019 merger — 3,800+ engineers across europe for large ml and digital transformation programmes. They also differ in team size (5,700+ vs 3,884), minimum engagement ($50K+ vs $50K+), and primary industries served (fintech, healthcare vs financial, healthcare).

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