Addepto vs micro1: full comparison for 2026
Quick verdict
Addepto (4.0/5) edges ahead of micro1 (3.7/5) overall. Addepto is the better choice for industrial and automotive companies that need data engineers who know factory data. micro1 is the stronger option for AI teams that need many vetted contributors quickly for evaluation or data work. The right choice depends on your project size, budget, and required tech stack.
Addepto vs micro1: head-to-head summary
| Criterion | Addepto | micro1 |
|---|---|---|
| Founded | 2017 | 2022 |
| HQ | Warsaw, Poland | California, USA |
| Team size | 50–249 | Estimates range from 11–50 staff to thousands including contractors |
| Rating | 4.0 / 5 | 3.7 / 5 |
| Primary differentiator | Data and ML engineers with industrial and automotive client history | Automated AI interviews that screen candidates in high volume |
| Pricing model | Monthly per engineer or project fee; rates on request | Hourly or monthly per contractor; one-week test option; rates on request |
| 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, SaaS, Finance, Healthcare |
Addepto vs micro1: 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.
micro1
micro1 was founded in 2022 by Ali Ansari and is based in California. Its AI recruiter, Zara, runs a structured interview of 20 to 40 minutes with every applicant. The company raised a Series A at a $500 million valuation in September 2025 and now earns most of its revenue supplying vetted experts to AI labs for model training. Engineering teams can still hire through it, but an automated interview is a different thing from a senior engineer reviewing code, and its focus has moved toward lab work.
Services and capabilities: Addepto vs micro1
| Capability | Addepto | micro1 |
|---|---|---|
| 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 micro1
| Framework / platform | Addepto | micro1 |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | 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 micro1
| Criterion | Addepto | micro1 |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Freelance contract, Trial period |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Addepto vs micro1
| Dimension | Addepto | micro1 |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Automotive, Aviation | AI labs, Technology, SaaS |
| Best use cases | Adding a data engineer to an automotive analytics platform, Building a predictive maintenance model with a two-person team | Hiring twenty LLM evaluators for a model release, Adding a contract ML engineer for a short project |
| Typical project type | Dedicated engineer | Freelance contract |
Addepto vs micro1: 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 |
| micro1 | |
|---|---|
| + | Can screen a very large number of candidates fast |
| + | Experience with AI-lab evaluation work |
| + | A short trial before a longer contract |
| - | AI interviews replace engineer judgment in the screen |
| - | Most revenue now comes from AI labs, not product teams |
| - | Headquarters is listed differently across sources |
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 micro1?
A typical fit: hiring twenty LLM evaluators for a model release.
Automated AI interviews that screen candidates in high volume. Minimum engagement is not publicly disclosed. Works best with clients in AI labs, Technology, SaaS, Finance, Healthcare.
Decision matrix: Addepto vs micro1
| 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 | micro1 |
| Your budget is at the lower end | Compare: Addepto (Not published) vs micro1 (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 micro1
| Use case | Addepto fit | micro1 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 twenty LLM evaluators for a model release | Limited | Strong | micro1 |
| Adding a contract ML engineer for a short project | Strong | Strong | Both equally |
Verdict: Addepto vs micro1
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.
micro1 (3.7/5) is worth a look if you need adding a contract ML engineer for a short project. If your situation matches that, micro1 is a competitive option.
Related comparisons
Addepto vs micro1 FAQ
Is Addepto better than micro1?
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. micro1's strongest advantage: can screen a very large number of candidates fast.
How do Addepto and micro1 differ in pricing?
Addepto uses monthly per engineer or project fee; rates on request pricing. micro1 uses hourly or monthly per contractor; one-week test option; 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: Addepto or micro1?
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 micro1?
Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. micro1's primary differentiator is: automated AI interviews that screen candidates in high volume. They also differ in team size (50–249 vs Estimates range from 11–50 staff to thousands including contractors), 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.