Addepto vs Mercor: full comparison for 2026
Quick verdict
Addepto (4.0/5) edges ahead of Mercor (3.7/5) overall. Addepto is the better choice for industrial and automotive companies that need data engineers who know factory data. Mercor is the stronger option for AI labs and research teams that need specialist contractors in large numbers. The right choice depends on your project size, budget, and required tech stack.
Addepto vs Mercor: head-to-head summary
| Criterion | Addepto | Mercor |
|---|---|---|
| Founded | 2017 | 2023 |
| HQ | Warsaw, Poland | San Francisco, California, USA |
| Team size | 50–249 | 300–400 staff; large contractor network |
| Rating | 4.0 / 5 | 3.7 / 5 |
| Primary differentiator | Data and ML engineers with industrial and automotive client history | AI-run interviews and matching built for high-volume expert hiring |
| Pricing model | Monthly per engineer or project fee; rates on request | Contractor rate plus platform fee (about 30%, Sacra estimate) |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Databricks, Spark | Python, PyTorch, OpenAI |
| Industries served | Manufacturing, Automotive, Aviation, Retail, Logistics | AI labs, Technology, Finance, Legal, Healthcare |
Addepto vs Mercor: overview
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.
Mercor
Mercor was founded in San Francisco in 2023 and uses AI interviews to screen applicants. It raised money at a $10 billion valuation in October 2025, mainly on the strength of supplying experts to AI labs for model training and evaluation. Product teams can hire engineers through it, but the platform is built for volume, and Sacra estimates its fee at about 30% of contractor pay. If you want two senior ML engineers for a year-long roadmap, look elsewhere. A firm that employs and manages its people fits that job better.
Services and capabilities: Addepto vs Mercor
| Capability | Addepto | Mercor |
|---|---|---|
| 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: Addepto vs Mercor
| Framework / platform | Addepto | Mercor |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | N/A |
| Databricks | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Addepto vs Mercor
| Criterion | Addepto | Mercor |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Freelance contract |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Addepto vs Mercor
| Dimension | Addepto | Mercor |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Automotive, Aviation | AI labs, Technology, Finance |
| Best use cases | Adding a data engineer to an automotive analytics platform, Building a predictive maintenance model with a two-person team | Hiring dozens of domain experts to evaluate a model, Adding a contract ML engineer for a research sprint |
| Typical project type | Dedicated engineer | Freelance contract |
Addepto vs Mercor: pros and cons
| 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 |
| Mercor | |
|---|---|
| + | Fast access to a large pool of specialists |
| + | Well funded |
| + | Experienced with AI-lab evaluation and training work |
| - | AI interviews, not engineers, do the first screen |
| - | Fee of about 30% adds up over a long engagement |
| - | Founded in 2023, so a short track record with product teams |
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.
Who should choose Mercor?
A typical fit: hiring dozens of domain experts to evaluate a model.
AI-run interviews and matching built for high-volume expert hiring. Minimum engagement is not publicly disclosed. Works best with clients in AI labs, Technology, Finance, Legal, Healthcare.
Decision matrix: Addepto vs Mercor
| 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 | Addepto |
| 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: Addepto (Not published) vs Mercor (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: Addepto vs Mercor
| Use case | Addepto fit | Mercor fit | Winner |
|---|---|---|---|
| Adding a data engineer to an automotive analytics platform | Strong | Strong | Both equally |
| Building a predictive maintenance model with a two-person team | Strong | Limited | Addepto |
| Hiring dozens of domain experts to evaluate a model | Limited | Strong | Mercor |
| Adding a contract ML engineer for a research sprint | Strong | Strong | Both equally |
Verdict: Addepto vs Mercor
Addepto (4.0/5) is the stronger overall choice for most AI Engineer Staffing projects. Data and ML engineers with industrial and automotive client history.
Mercor (3.7/5) is worth a look if you need adding a contract ML engineer for a research sprint. If your situation matches that, Mercor is a competitive option.
Related comparisons
Addepto vs Mercor FAQ
Is Addepto better than Mercor?
Addepto (4.0/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: strong data engineering on Databricks and Azure. Mercor's strongest advantage: fast access to a large pool of specialists.
How do Addepto and Mercor differ in pricing?
Addepto uses monthly per engineer or project fee; rates on request pricing. Mercor uses contractor rate plus platform fee (about 30%, sacra estimate) pricing. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Addepto or Mercor?
Mercor 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 Mercor?
Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. Mercor's primary differentiator is: AI-run interviews and matching built for high-volume expert hiring. They also differ in team size (50–249 vs 300–400 staff; large contractor network), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Automotive vs AI labs, Technology).
Verify all details directly with each company before making a decision.