Turing vs Addepto: full comparison for 2026
Quick verdict
Turing (4.1/5) edges ahead of Addepto (4.0/5) overall. Turing is the better choice for companies that need many remote ML and data engineers quickly and value speed over hand-picked screening. Addepto is the stronger option for industrial and automotive companies that need data engineers who know factory data. The right choice depends on your project size, budget, and required tech stack.
Turing vs Addepto: head-to-head summary
| Criterion | Turing | Addepto |
|---|---|---|
| Founded | 2018 | 2017 |
| HQ | Palo Alto, California, USA | Warsaw, Poland |
| Team size | Staff size not published; multi-million talent pool | 50–249 |
| Rating | 4.1 / 5 | 4.0 / 5 |
| Primary differentiator | Automated vetting and matching across the largest developer pool on this page | Data and ML engineers with industrial and automotive client history |
| Pricing model | Monthly or hourly per developer; no public rate card; rates on request | Monthly per engineer or project fee; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Databricks, Spark |
| Industries served | Technology, AI labs, Finance, Healthcare, Retail | Manufacturing, Automotive, Aviation, Retail, Logistics |
Turing vs Addepto: overview
Turing
Turing was founded in Palo Alto in 2018 and built its developer marketplace on automated vetting. A company executive has said its system evaluated about two million developers and passed more than 50,000 through technical exams and interviews. That machinery makes it fast for common roles. Its business has shifted, though: much of its revenue now comes from producing training data for AI labs, and in 2026 it recruits doctors and accountants for that work alongside engineers. Third-party guides estimate $100 to $200 an hour for mid to senior developers, but Turing publishes no rate card.
Addepto
Addepto was founded in Warsaw in 2017 and works on AI, ML and data engineering, mostly for industrial and automotive clients. KMS Technology acquired it in December 2025, so it now sits inside a larger U.S.-based IT group. Addepto supplies data and ML engineers for team extension as well as running projects. The acquisition may widen its bench over time, but buyers should expect changes to contracts and account management as the integration proceeds.
Services and capabilities: Turing vs Addepto
| Capability | Turing | Addepto |
|---|---|---|
| ML engineers | ✓ | ✓ |
| LLM / GenAI engineers | ✓ | ✓ |
| AI agent developers | ✗ | ✗ |
| MLOps engineers | ✗ | ✗ |
| Computer vision engineers | ✗ | ✗ |
| NLP engineers | ✗ | ✗ |
| Data engineers | ✓ | ✓ |
| Engineer-led technical screen | ✗ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✗ |
| Nearshore time-zone overlap | ✗ | ✗ |
| Direct hire option | ✗ | ✗ |
Tech stack comparison: Turing vs Addepto
| Framework / platform | Turing | Addepto |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Turing vs Addepto
| Criterion | Turing | Addepto |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Freelance contract | Dedicated engineer, Dedicated team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Turing vs Addepto
| Dimension | Turing | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Technology, AI labs, Finance | Manufacturing, Automotive, Aviation |
| Best use cases | Adding five remote data engineers to a cloud migration, Staffing an LLM evaluation project with many short-term contributors | Adding a data engineer to an automotive analytics platform, Building a predictive maintenance model with a two-person team |
| Typical project type | Dedicated engineer | Dedicated engineer |
Turing vs Addepto: pros and cons
| Turing | |
|---|---|
| + | Can match many engineers at once across time zones |
| + | Huge pool makes rare stack combinations easier to find |
| + | Experience supplying engineers to AI labs |
| - | Vetting is mostly automated, with less human technical judgment than engineer-led screens |
| - | Revenue now leans toward AI training data, which may pull attention from staffing clients |
| - | No published rates; third-party estimates are high |
| Addepto | |
|---|---|
| + | Strong data engineering on Databricks and Azure |
| + | Industrial and automotive references |
| + | Backing from a larger group may add capacity |
| - | Acquired by KMS Technology in December 2025, so terms and contacts may change |
| - | Fewer computer-vision and NLP specialists than AI-research firms |
| - | Staffing evidence is thinner than its project work |
Who should choose Turing?
A typical fit: adding five remote data engineers to a cloud migration.
Automated vetting and matching across the largest developer pool on this page. Minimum engagement is not publicly disclosed. Works best with clients in Technology, AI labs, Finance, Healthcare, Retail.
Who should choose Addepto?
A typical fit: adding a data engineer to an automotive analytics platform.
Data and ML engineers with industrial and automotive client history. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Automotive, Aviation, Retail, Logistics.
Decision matrix: Turing vs Addepto
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Neither documents an engineer-led screen; run your own technical interview |
| You need one specialist for a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Both; Turing rates higher overall |
| You want to test an engineer before committing | Neither publishes a trial; negotiate a short first term |
| Your budget is at the lower end | Compare: Turing (Not published) vs Addepto (Not published) |
| Your team works U.S. hours | Neither lists Latin American engineers; confirm overlap hours in the contract |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
Use case fit: Turing vs Addepto
| Use case | Turing fit | Addepto fit | Winner |
|---|---|---|---|
| Adding five remote data engineers to a cloud migration | Strong | Strong | Both equally |
| Staffing an LLM evaluation project with many short-term contributors | Strong | Strong | Both equally |
| Adding a data engineer to an automotive analytics platform | Strong | Strong | Both equally |
| Building a predictive maintenance model with a two-person team | Limited | Strong | Addepto |
Verdict: Turing vs Addepto
Turing (4.1/5) is the stronger overall choice for most AI Engineer Staffing projects. Automated vetting and matching across the largest developer pool on this page.
Addepto (4.0/5) is worth a look if you need building a predictive maintenance model with a two-person team. If your situation matches that, Addepto is a competitive option.
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Turing vs Addepto FAQ
Is Turing better than Addepto?
Turing (4.1/5) scores higher overall, but "better" depends on your use case. Turing's strongest advantage: can match many engineers at once across time zones. Addepto's strongest advantage: strong data engineering on Databricks and Azure.
How do Turing and Addepto differ in pricing?
Turing uses monthly or hourly per developer; no public rate card; rates on request pricing. Addepto uses monthly per engineer or project fee; rates on request pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Turing or Addepto?
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 Turing and Addepto?
Turing's primary differentiator is: automated vetting and matching across the largest developer pool on this page. Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. They also differ in team size (Staff size not published; multi-million talent pool vs 50–249), minimum engagement (Not published vs Not published), and primary industries served (Technology, AI labs vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.