Best Machine Learning Agencies

RTS Labs vs Yalantis: full comparison for 2026

Last updated: July 2026

Quick verdict

RTS Labs (4.1/5) edges ahead of Yalantis (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. Yalantis is the stronger option for healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering. The right choice depends on your project size, budget, and required tech stack.

RTS Labs vs Yalantis: head-to-head summary

Criterion RTS Labs Yalantis
Founded 2010 2008
HQ Richmond, VA Kyiv, Ukraine
Team size 50–150 200–400
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 Healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering
Pricing model Fixed project, T&M Fixed project, T&M
Min. engagement $20K+ $25K+
Primary tech stack Python, Azure, AWS Python, TensorFlow, PyTorch
Industries served financial, healthcare, manufacturing, logistics, saas healthcare, fintech, saas, logistics, manufacturing

RTS Labs vs Yalantis: 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.)

Yalantis

Yalantis was founded in 2008 and operates with a focus on compliance-first IoT and software engineering alongside machine learning consulting. The company's ML team provides domain-specific consulting, model deployment, and ongoing support, with depth in regulated industries including healthcare and fintech. ML consultants hold master's degrees in machine learning and have production data science experience. (Founded year per Tracxn; specialisation per Yalantis official website.)

Services and capabilities: RTS Labs vs Yalantis

Capability RTS Labs Yalantis
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 Yalantis

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

Pricing comparison: RTS Labs vs Yalantis

Criterion RTS Labs Yalantis
Minimum engagement $20K+ $25K+
Engagement models Fixed project, T&M Fixed project, T&M, Retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: RTS Labs vs Yalantis

Dimension RTS Labs Yalantis
Best company size Startup to mid-market Startup to mid-market
Best industries financial, healthcare, manufacturing healthcare, fintech, saas
Best use cases ML-powered financial fraud detection, Healthcare data pipeline and predictive analytics Compliance-aware ML model for healthcare data, Predictive analytics for fintech risk management
Typical project type Fixed project Fixed project

RTS Labs vs Yalantis: 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
Yalantis
+ Compliance-first approach for regulated healthcare and fintech projects
+ Full-lifecycle ML: from consulting through deployment and support
+ Master's-qualified ML consultants — verifiable technical depth
+ IoT integration experience alongside ML — rare combination
- Ukraine-based delivery carries geographic risk considerations for some clients
- Less suited to pure data science research or exploratory projects

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 Yalantis?

Yalantis is the right choice for healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering.

Compliance-first ML delivery — particularly strong for healthcare and regulated fintech with IoT integration needs. Minimum engagement starts at $25K+. Works best with clients in healthcare, fintech, saas, logistics, manufacturing.

Decision matrix: RTS Labs vs Yalantis

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 Check each company's engagement model
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 Yalantis

Use case RTS Labs fit Yalantis fit Winner
ML-powered financial fraud detection Strong Limited RTS Labs
Healthcare data pipeline and predictive analytics Strong Strong Both equally
Compliance-aware ML model for healthcare data Limited Strong Yalantis
Predictive analytics for fintech risk management Strong Strong Both equally
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: RTS Labs vs Yalantis

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.

Yalantis (3.9/5) is the better choice when healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering. If your situation matches those criteria, Yalantis is a competitive option.

Related comparisons

RTS Labs vs Yalantis FAQ

Is RTS Labs better than Yalantis?

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. Yalantis is better for healthcare and fintech companies needing compliance-aware ML consulting paired with IoT or embedded engineering.

How do RTS Labs and Yalantis differ in pricing?

RTS Labs uses fixed project, t&m pricing with a minimum engagement of $20K+. Yalantis uses fixed project, t&m pricing with a minimum engagement of $25K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: RTS Labs or Yalantis?

Yalantis 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 Yalantis?

RTS Labs's primary differentiator is: pilot-to-production ml with deep data engineering roots — snowflake, azure, and aws native. Yalantis's primary differentiator is: compliance-first ml delivery — particularly strong for healthcare and regulated fintech with iot integration needs. They also differ in team size (50–150 vs 200–400), minimum engagement ($20K+ vs $25K+), and primary industries served (financial, healthcare vs healthcare, fintech).

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