Addepto vs Turing: full comparison for 2026
Last updated: July 2026
Quick verdict
Addepto (4.2/5) edges ahead of Turing (3.7/5) overall. Addepto is the better choice for mid-market companies in finance, energy, or retail needing bespoke ML models with full data pipeline support and sector-specific regulatory awareness. Turing is the stronger option for teams that need to extend their ML engineering capacity with pre-vetted senior developers, without the overhead of a full delivery engagement. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Turing: head-to-head summary
| Criterion | Addepto | Turing |
|---|---|---|
| Founded | 2016 | 2018 |
| HQ | Warsaw, Poland | Palo Alto, CA, USA |
| Team size | 50–200 | 1,000+ |
| Rating | 4.2 / 5 | 3.7 / 5 |
| Best for | Mid-market companies in finance, energy, or retail needing bespoke ML models with full data pipeline support and sector-specific regulatory awareness | Teams that need to extend their ML engineering capacity with pre-vetted senior developers, without the overhead of a full delivery engagement |
| Pricing model | Fixed project, T&M, Dedicated team | Staff augmentation |
| Min. engagement | $20K | $8K/month per developer |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | fintech, energy, retail, manufacturing, logistics | SaaS, fintech, healthcare, retail, manufacturing |
Addepto vs Turing: overview
Addepto
Addepto is a Poland-based AI consulting and development firm focused on end-to-end machine learning solutions for mid-market and enterprise clients. The company specializes in building data pipelines, custom ML models, and decision-support tools with particular depth in financial services, energy, and retail — industries where regulatory awareness and data governance are non-negotiable. Addepto covers the full stack from data engineering through model development, deployment, and integration.
Turing
Turing is an AI-powered software talent platform founded in 2018 and headquartered in Palo Alto, California. The company employs 1,000+ internal staff and provides access to 3M+ global ML developers, using AI-driven vetting to place what it claims are top 1% developers directly into client engineering teams (per company website; independently unverifiable). Turing charges $49–$150+ per hour depending on developer level. Unlike delivery firms, Turing provides individual developers — clients manage the ML programme themselves.
Services and capabilities: Addepto vs Turing
| Capability | Addepto | Turing |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Deep learning | ✓ | ✓ |
| NLP | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| MLOps | ✗ | ✗ |
| Predictive analytics | ✓ | ✓ |
| Generative AI | ✓ | ✗ |
| Data engineering | ✓ | ✗ |
| Staff augmentation | ✗ | ✓ |
Tech stack comparison: Addepto vs Turing
| Framework / platform | Addepto | Turing |
|---|---|---|
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| Scikit-Learn | ✓ | ✓ |
| LangChain | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
| GCP Vertex AI | N/A | N/A |
| Kubernetes | N/A | ✓ |
| Apache Spark | ✓ | N/A |
| MLflow | N/A | N/A |
Pricing comparison: Addepto vs Turing
| Criterion | Addepto | Turing |
|---|---|---|
| Minimum engagement | $20K | $8K/month per developer |
| Engagement models | Fixed project, T&M, Dedicated team | Staff augmentation |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Addepto vs Turing
| Dimension | Addepto | Turing |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | fintech, energy, retail | SaaS, fintech, healthcare |
| Best use cases | Credit risk scoring and fraud detection model development for fintech platforms, Energy demand forecasting and grid optimization using time-series ML models | Extending an internal ML engineering team with a pre-vetted senior ML engineer, Staff augmentation for a specific deep learning or NLP specialization not in-house |
| Typical project type | Fixed project | Staff augmentation |
Addepto vs Turing: pros and cons
| Addepto | |
|---|---|
| + | Genuine depth in finance and energy ML — not a generalist firm claiming vertical expertise |
| + | Covers the full stack from data pipeline architecture through model deployment |
| + | Generative AI capability alongside classical ML for hybrid solution architectures |
| + | Warsaw delivery hub provides competitive rates with EU-based data handling |
| + | Accessible minimum engagement for early-stage ML projects or POCs |
| - | Smaller team than enterprise-tier firms; large-scale concurrent programmes may strain capacity |
| - | Less US-based client management than North American competitors |
| - | Limited public case studies compared to larger firms with dedicated marketing teams |
| Turing | |
|---|---|
| + | Access to 3M+ global ML developer pool — highest candidate diversity of any firm in this list |
| + | AI-powered vetting reduces hiring time vs traditional recruitment processes |
| + | Competitive rates ($49–$150/hr) for individual senior ML developers working in client teams |
| + | Flexible engagement — can scale individual developers up or down monthly |
| + | Developers work directly in client engineering culture and tooling stack |
| - | Talent platform, not a delivery firm — clients must manage the ML programme themselves |
| - | Top 1% selection claim is per company website only — independently unverifiable |
| - | No project management, architecture, or delivery ownership — engagements require internal technical leadership |
Who should choose Addepto?
Addepto is the right choice for mid-market companies in finance, energy, or retail needing bespoke ML models with full data pipeline support and sector-specific regulatory awareness.
End-to-end AI/ML delivery with particular sector depth in financial services and energy — industries that require compliance sophistication alongside technical capability. Minimum engagement starts at $20K. Works best with clients in fintech, energy, retail, manufacturing, logistics.
Who should choose Turing?
Turing is the right choice for teams that need to extend their ML engineering capacity with pre-vetted senior developers, without the overhead of a full delivery engagement.
AI-powered vetting platform screening 3M+ global ML developers to place the top 1% directly in client engineering teams at rates competitive with US in-house hiring. Minimum engagement starts at $8K/month per developer. Works best with clients in SaaS, fintech, healthcare, retail, manufacturing.
Decision matrix: Addepto vs Turing
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Addepto |
| You need a large dedicated team for an ongoing programme | Addepto |
| Your budget is at the lower end | Turing |
| You need specialist depth in a specific vertical | Addepto |
| You need staff augmentation or team extension | Turing |
| You need consulting before committing to a build | Addepto |
Use case fit: Addepto vs Turing
| Use case | Addepto fit | Turing fit | Winner |
|---|---|---|---|
| Credit risk scoring and fraud detection model development for fintech platforms | Strong | Limited | Addepto |
| Energy demand forecasting and grid optimization using time-series ML models | Strong | Limited | Addepto |
| Extending an internal ML engineering team with a pre-vetted senior ML engineer | Limited | Strong | Turing |
| Staff augmentation for a specific deep learning or NLP specialization not in-house | Limited | Strong | Turing |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Strong | Turing |
Verdict: Addepto vs Turing
Addepto (4.2/5) is the stronger overall choice for most Machine Learning Development projects. End-to-end AI/ML delivery with particular sector depth in financial services and energy — industries that require compliance sophistication alongside technical capability. It is best for mid-market companies in finance, energy, or retail needing bespoke ML models with full data pipeline support and sector-specific regulatory awareness.
Turing (3.7/5) is the better choice when teams that need to extend their ML engineering capacity with pre-vetted senior developers, without the overhead of a full delivery engagement. If your situation matches those criteria, Turing is a competitive option.
Related comparisons
Addepto vs Turing FAQ
Is Addepto better than Turing?
Addepto (4.2/5) scores higher overall, but "better" depends on your use case. Addepto is better for mid-market companies in finance, energy, or retail needing bespoke ML models with full data pipeline support and sector-specific regulatory awareness. Turing is better for teams that need to extend their ML engineering capacity with pre-vetted senior developers, without the overhead of a full delivery engagement.
How do Addepto and Turing differ in pricing?
Addepto uses fixed project, t&m, dedicated team pricing with a minimum engagement of $20K. Turing uses staff augmentation pricing with a minimum engagement of $8K/month per developer. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or Turing?
Addepto is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between Addepto and Turing?
Addepto's primary differentiator is: end-to-end ai/ml delivery with particular sector depth in financial services and energy — industries that require compliance sophistication alongside technical capability. Turing's primary differentiator is: ai-powered vetting platform screening 3m+ global ml developers to place the top 1% directly in client engineering teams at rates competitive with us in-house hiring. They also differ in team size (50–200 vs 1,000+), minimum engagement ($20K vs $8K/month per developer), and primary industries served (fintech, energy vs SaaS, fintech).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.