Best Machine Learning Agencies

RTS Labs vs DataArt: full comparison for 2026

Last updated: July 2026

Quick verdict

RTS Labs (4.1/5) edges ahead of DataArt (3.9/5) overall. RTS Labs is the better choice for uS mid-market companies in financial services and healthcare needing AI from pilot to production on Azure or AWS. 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.

RTS Labs vs DataArt: head-to-head summary

Criterion RTS Labs DataArt
Founded 2010 1997
HQ Richmond, VA New York, NY
Team size 50–150 5,700+
Rating 4.1 / 5 3.9 / 5
Best for US mid-market companies in financial services and healthcare needing AI from pilot to production on Azure or AWS 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 $20K+ $50K+
Primary tech stack Python, Azure, AWS Python, TensorFlow, PyTorch
Industries served financial, healthcare, manufacturing, logistics, saas fintech, healthcare, travel, media, retail

RTS Labs vs DataArt: overview

RTS Labs

RTS Labs was founded in 2010 and is headquartered in Richmond, Virginia. The firm specialises in AI and ML projects from pilot to production, with strong roots in data engineering — pipelines, warehousing, and integration. Core platforms include Azure, AWS, Salesforce, and Snowflake, with ML applied to financial services, healthcare, and manufacturing use cases. RTS Labs has been ranked a top ML consulting firm for mid-sized US businesses. (Founding year and specialisation per RTS Labs official website.)

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: RTS Labs vs DataArt

Capability RTS Labs 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: RTS Labs vs DataArt

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

Pricing comparison: RTS Labs vs DataArt

Criterion RTS Labs DataArt
Minimum engagement $20K+ $50K+
Engagement models Fixed project, T&M T&M, Dedicated team, Retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: RTS Labs vs DataArt

Dimension RTS Labs DataArt
Best company size Startup to mid-market Startup to mid-market
Best industries financial, healthcare, manufacturing fintech, healthcare, travel
Best use cases ML-powered financial fraud detection, Healthcare data pipeline and predictive analytics ML feature integration into existing fintech platform, Travel recommendation engine
Typical project type Fixed project T&M

RTS Labs vs DataArt: pros and cons

RTS Labs
+ Pilot-to-production ML ownership — not just consulting deliverables
+ Strong data engineering base: pipelines, warehousing, Snowflake, dbt
+ Azure and AWS native with Salesforce integration experience
+ US-based with financial services and healthcare domain knowledge
+ Practical, outcome-focused approach for mid-market budgets
- Smaller team limits concurrent large programmes
- Less international delivery footprint than larger firms
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 RTS Labs?

RTS Labs is the right choice for uS mid-market companies in financial services and healthcare needing AI from pilot to production on Azure or AWS.

Pilot-to-production ML with deep data engineering roots — Snowflake, Azure, and AWS native. Minimum engagement starts at $20K+. Works best with clients in financial, healthcare, manufacturing, logistics, saas.

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: RTS Labs vs DataArt

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

Use case fit: RTS Labs vs DataArt

Use case RTS Labs fit DataArt fit Winner
ML-powered financial fraud detection Strong Limited RTS Labs
Healthcare data pipeline and predictive analytics Strong Strong Both equally
ML feature integration into existing fintech platform Strong Strong Both equally
Travel recommendation engine Limited Strong DataArt
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: RTS Labs vs DataArt

RTS Labs (4.1/5) is the stronger overall choice for most Machine Learning projects. Pilot-to-production ML with deep data engineering roots — Snowflake, Azure, and AWS native. It is best for uS mid-market companies in financial services and healthcare needing AI from pilot to production on Azure or AWS.

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

RTS Labs vs DataArt FAQ

Is RTS Labs better than DataArt?

RTS Labs (4.1/5) scores higher overall, but "better" depends on your use case. RTS Labs is better for uS mid-market companies in financial services and healthcare needing AI from pilot to production on Azure or AWS. DataArt is better for enterprises wanting ML services from a large, established software engineering firm with fintech or travel domain depth.

How do RTS Labs and DataArt differ in pricing?

RTS Labs uses fixed project, t&m pricing with a minimum engagement of $20K+. 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: RTS Labs or DataArt?

RTS Labs 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 RTS Labs and DataArt?

RTS Labs's primary differentiator is: pilot-to-production ml with deep data engineering roots — snowflake, azure, and aws native. 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 (50–150 vs 5,700+), minimum engagement ($20K+ vs $50K+), and primary industries served (financial, healthcare vs fintech, healthcare).

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