RTS Labs vs Keyrus: full comparison for 2026
Last updated: July 2026
Quick verdict
RTS Labs (4.1/5) edges ahead of Keyrus (3.8/5) 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. Keyrus is the stronger option for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. The right choice depends on your project size, budget, and required tech stack.
RTS Labs vs Keyrus: head-to-head summary
| Criterion | RTS Labs | Keyrus |
|---|---|---|
| Founded | 2010 | 2000 |
| HQ | Richmond, VA | Paris, France |
| Team size | 50–150 | 3,500+ |
| Rating | 4.1 / 5 | 3.8 / 5 |
| Best for | US mid-market companies in financial services and healthcare needing AI from pilot to production on Azure or AWS | International enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience |
| Pricing model | Fixed project, T&M | T&M, retainer |
| Min. engagement | $20K+ | $50K+ |
| Primary tech stack | Python, Azure, AWS | Python, Tableau, Power BI |
| Industries served | financial, healthcare, manufacturing, logistics, saas | financial, retail, healthcare, manufacturing, media |
RTS Labs vs Keyrus: 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.)
Keyrus
Keyrus is an international consulting group founded in 2000, headquartered in Paris, France, and operating in over 20 countries with 3,500+ professionals. The company positions itself at the intersection of business, data, and AI — helping clients move from experimental AI to industrial-grade ML systems in production. Services span data strategy, BI, analytics, AI testing, and ML deployment. (Employee count and global footprint per Keyrus official website.)
Services and capabilities: RTS Labs vs Keyrus
| Capability | RTS Labs | Keyrus |
|---|---|---|
| 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 Keyrus
| Framework / platform | RTS Labs | Keyrus |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| PyTorch | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: RTS Labs vs Keyrus
| Criterion | RTS Labs | Keyrus |
|---|---|---|
| Minimum engagement | $20K+ | $50K+ |
| Engagement models | Fixed project, T&M | T&M, Retainer, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: RTS Labs vs Keyrus
| Dimension | RTS Labs | Keyrus |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | financial, healthcare, manufacturing | financial, retail, healthcare |
| Best use cases | ML-powered financial fraud detection, Healthcare data pipeline and predictive analytics | Industrial AI deployment at enterprise scale, Analytics and ML platform for financial services |
| Typical project type | Fixed project | T&M |
RTS Labs vs Keyrus: 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 |
| Keyrus | |
|---|---|
| + | Global footprint: 20+ countries, 3,500+ professionals |
| + | Industrial-AI focus — moves clients from PoC to production scale |
| + | Strong analytics and BI alongside ML for full data stack coverage |
| + | AI testing and validation capability |
| - | Large-firm pricing not suited to startup or SMB budgets |
| - | AI is one offering within broader data consulting — not ML-first |
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 Keyrus?
Keyrus is the right choice for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.
From experimental AI to industrial AI — consulting group specialising in productionising ML for large organisations. Minimum engagement starts at $50K+. Works best with clients in financial, retail, healthcare, manufacturing, media.
Decision matrix: RTS Labs vs Keyrus
| 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 | Keyrus |
| 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 Keyrus
| Use case | RTS Labs fit | Keyrus fit | Winner |
|---|---|---|---|
| ML-powered financial fraud detection | Strong | Limited | RTS Labs |
| Healthcare data pipeline and predictive analytics | Strong | Limited | RTS Labs |
| Industrial AI deployment at enterprise scale | Limited | Strong | Keyrus |
| Analytics and ML platform for financial services | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: RTS Labs vs Keyrus
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.
Keyrus (3.8/5) is the better choice when international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. If your situation matches those criteria, Keyrus is a competitive option.
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RTS Labs vs Keyrus FAQ
Is RTS Labs better than Keyrus?
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. Keyrus is better for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.
How do RTS Labs and Keyrus differ in pricing?
RTS Labs uses fixed project, t&m pricing with a minimum engagement of $20K+. Keyrus 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: RTS Labs or Keyrus?
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 Keyrus?
RTS Labs's primary differentiator is: pilot-to-production ml with deep data engineering roots — snowflake, azure, and aws native. Keyrus's primary differentiator is: from experimental ai to industrial ai — consulting group specialising in productionising ml for large organisations. They also differ in team size (50–150 vs 3,500+), minimum engagement ($20K+ vs $50K+), and primary industries served (financial, healthcare vs financial, retail).
Last reviewed: July 2026. Verify all details directly with each agency before making a decision.