Best Machine Learning Agencies

Miquido vs DataArt: full comparison for 2026

Last updated: July 2026

Quick verdict

Miquido (4.2/5) edges ahead of DataArt (3.9/5) overall. Miquido is the better choice for product companies and scale-ups needing ML features embedded within polished mobile or web products. DataArt is the stronger option for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. The right choice depends on your project size, budget, and required tech stack.

Miquido vs DataArt: head-to-head summary

Criterion Miquido DataArt
Founded 2011 1997
HQ Kraków, Poland New York, NY
Team size 200+ 5,700+
Rating 4.2 / 5 3.9 / 5
Best for Product companies and scale-ups needing ML features embedded within polished mobile or web products Enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth
Pricing model Fixed project, T&M T&M, dedicated team
Min. engagement $25K+ $50K+
Primary tech stack Python, TensorFlow, PyTorch Python, TensorFlow, PyTorch
Industries served saas, media, retail, healthcare, fintech fintech, healthcare, travel, media, retail

Miquido vs DataArt: overview

Miquido

Miquido was founded in 2011 and is headquartered in Kraków, Poland, with 200+ engineers. The company specialises in AI and ML development integrated within mobile and web product engineering, serving clients including Skyscanner and Abbey Road Studios (per Miquido Clutch profile and official website). Miquido is known for combining UI/UX engineering with AI capabilities — particularly computer vision, recommendation systems, and NLP — for product-driven clients.

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.)

Services and capabilities: Miquido vs DataArt

Capability Miquido DataArt
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: Miquido vs DataArt

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

Pricing comparison: Miquido vs DataArt

Criterion Miquido DataArt
Minimum engagement $25K+ $50K+
Engagement models Fixed project, T&M, Retainer T&M, Dedicated team, Retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: Miquido vs DataArt

Dimension Miquido DataArt
Best company size Startup to mid-market Startup to mid-market
Best industries saas, media, retail fintech, healthcare, travel
Best use cases AI features within mobile travel app, Recommendation system for media platform ML feature integration into existing fintech platform, Travel recommendation engine
Typical project type Fixed project T&M

Miquido vs DataArt: pros and cons

Miquido
+ Strong integration of ML with product and UI engineering — rare combination
+ Named clients include Skyscanner and Abbey Road Studios
+ Full product lifecycle capability: design to ML to mobile/web delivery
+ Kraków studio with transparent pricing and verifiable Clutch reviews
+ Computer vision and NLP experience in production applications
- Less suitable for standalone ML research or data science consulting
- Product engineering focus means less depth in MLOps or large-scale data infrastructure
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

Who should choose Miquido?

Miquido is the right choice for product companies and scale-ups needing ML features embedded within polished mobile or web products.

AI-plus-product development — ML capabilities integrated with UX engineering, not delivered as a standalone model. Minimum engagement starts at $25K+. Works best with clients in saas, media, retail, healthcare, fintech.

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.

Decision matrix: Miquido vs DataArt

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

Use case fit: Miquido vs DataArt

Use case Miquido fit DataArt fit Winner
AI features within mobile travel app Strong Limited Miquido
Recommendation system for media platform Strong Strong Both equally
ML feature integration into existing fintech platform Limited Strong DataArt
Travel recommendation engine Strong Strong Both equally
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: Miquido vs DataArt

Miquido (4.2/5) is the stronger overall choice for most Machine Learning projects. AI-plus-product development — ML capabilities integrated with UX engineering, not delivered as a standalone model. It is best for product companies and scale-ups needing ML features embedded within polished mobile or web products.

DataArt (3.9/5) is the better choice when enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth. If your situation matches those criteria, DataArt is a competitive option.

Related comparisons

Miquido vs DataArt FAQ

Is Miquido better than DataArt?

Miquido (4.2/5) scores higher overall, but "better" depends on your use case. Miquido is better for product companies and scale-ups needing ML features embedded within polished mobile or web products. DataArt is better for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth.

How do Miquido and DataArt differ in pricing?

Miquido uses fixed project, t&m pricing with a minimum engagement of $25K+. DataArt 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: Miquido or DataArt?

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 Miquido and DataArt?

Miquido's primary differentiator is: ai-plus-product development — ml capabilities integrated with ux engineering, not delivered as a standalone model. DataArt's primary differentiator is: 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ml and software in fintech and travel. They also differ in team size (200+ vs 5,700+), minimum engagement ($25K+ vs $50K+), and primary industries served (saas, media vs fintech, healthcare).

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