Best Machine Learning Agencies

Keyrus vs Turing: full comparison for 2026

Last updated: July 2026

Quick verdict

Keyrus (3.8/5) edges ahead of Turing (3.8/5) overall. Keyrus is the better choice for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. Turing is the stronger option for companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension. The right choice depends on your project size, budget, and required tech stack.

Keyrus vs Turing: head-to-head summary

Criterion Keyrus Turing
Founded 2000 2018
HQ Paris, France Palo Alto, CA
Team size 3,500+ 6,859
Rating 3.8 / 5 3.8 / 5
Best for International enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience Companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension
Pricing model T&M, retainer Dedicated team, T&M
Min. engagement $50K+ Not disclosed
Primary tech stack Python, Tableau, Power BI Python, TensorFlow, PyTorch
Industries served financial, retail, healthcare, manufacturing, media saas, fintech, healthcare, retail, financial

Keyrus vs Turing: overview

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.)

Turing

Turing was founded in 2018 by Jonathan Siddharth and Rohan Aroe and is headquartered in Palo Alto, California. The company operates as an AI-powered talent marketplace and technology services firm with a network of 4M+ vetted software engineers, data scientists, and STEM experts. Turing has raised $247M at a $2.2B valuation from WestBridge Capital and Foundation Capital, and serves 1,000+ clients including Fortune 500 companies and governments. Note: Turing is primarily a talent marketplace — clients provide direction; Turing supplies vetted engineers rather than owning ML delivery outcomes. (Funding, valuation, and client count per Turing official website and Crunchbase.)

Services and capabilities: Keyrus vs Turing

Capability Keyrus Turing
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: Keyrus vs Turing

Framework / platform Keyrus Turing
Python
TensorFlow N/A
PyTorch N/A
AWS SageMaker N/A N/A
Azure ML N/A N/A

Pricing comparison: Keyrus vs Turing

Criterion Keyrus Turing
Minimum engagement $50K+ Not disclosed
Engagement models T&M, Retainer, Dedicated team T&M, Dedicated team
Rate transparency Minimum disclosed Not public
Price tier Accessible Mid-market

Target audience comparison: Keyrus vs Turing

Dimension Keyrus Turing
Best company size Startup to mid-market Startup to mid-market
Best industries financial, retail, healthcare saas, fintech, healthcare
Best use cases Industrial AI deployment at enterprise scale, Analytics and ML platform for financial services Staff augmentation for ML engineering team, Rapid placement of vetted data scientists
Typical project type T&M T&M

Keyrus vs Turing: pros and cons

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
Turing
+ 4M+ AI-vetted engineers — largest pre-screened ML talent pool in the category
+ $2.2B valuation with $247M raised — stable platform with institutional backing
+ 1,000+ clients including Fortune 500 and government organisations
+ Fastest path to pre-screened ML engineer placement
- Talent marketplace model — Turing supplies engineers; client provides direction and owns outcomes
- Less suited to projects needing a delivery firm with end-to-end accountability
- Delivery quality depends on client PM capability — not owned by Turing

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.

Who should choose Turing?

Turing is the right choice for companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension.

AI-vetted 4M+ developer network — fastest route to pre-screened ML talent for staff augmentation. Minimum engagement starts at Not disclosed. Works best with clients in saas, fintech, healthcare, retail, financial.

Decision matrix: Keyrus vs Turing

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 Keyrus
Your budget is at the lower end Compare: Keyrus ($50K+) vs Turing (Not disclosed)
You need specialist depth in a specific vertical Keyrus
You need staff augmentation or team extension Turing
You need consulting before committing to a build Keyrus

Use case fit: Keyrus vs Turing

Use case Keyrus fit Turing fit Winner
Industrial AI deployment at enterprise scale Strong Limited Keyrus
Analytics and ML platform for financial services Strong Limited Keyrus
Staff augmentation for ML engineering team Limited Strong Turing
Rapid placement of vetted data scientists Limited Strong Turing
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Strong Turing

Verdict: Keyrus vs Turing

Keyrus (3.8/5) is the stronger overall choice for most Machine Learning projects. From experimental AI to industrial AI — consulting group specialising in productionising ML for large organisations. It is best for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience.

Turing (3.8/5) is the better choice when companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension. If your situation matches those criteria, Turing is a competitive option.

Related comparisons

Keyrus vs Turing FAQ

Is Keyrus better than Turing?

Keyrus (3.8/5) scores higher overall, but "better" depends on your use case. Keyrus is better for international enterprises seeking a global data and AI consulting partner with industrial-AI implementation experience. Turing is better for companies needing rapid access to vetted ML engineers or data scientists for staff augmentation or team extension.

How do Keyrus and Turing differ in pricing?

Keyrus uses t&m, retainer pricing with a minimum engagement of $50K+. Turing uses dedicated team, t&m pricing with a minimum engagement of Not disclosed. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: Keyrus or Turing?

Turing 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 Keyrus and Turing?

Keyrus's primary differentiator is: from experimental ai to industrial ai — consulting group specialising in productionising ml for large organisations. Turing's primary differentiator is: ai-vetted 4m+ developer network — fastest route to pre-screened ml talent for staff augmentation. They also differ in team size (3,500+ vs 6,859), minimum engagement ($50K+ vs Not disclosed), and primary industries served (financial, retail vs saas, fintech).

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