Addepto vs micro1: full comparison for 2026
Quick verdict
Addepto (3.9/5) edges ahead of micro1 (3.8/5) overall. Addepto is the better choice for industrial and automotive companies adding AI and data engineers to an internal team. micro1 is the stronger option for startups that want vetted remote AI developers quickly, with payroll handled. 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 | San Francisco, California, USA |
| Team size | 50–99 (directory estimate) | Staff not confirmed; 3,000+ vetted engineers (per company) |
| Rating | 3.9 / 5 | 3.8 / 5 |
| Primary differentiator | AI-heavy team with manufacturing domain experience, now backed by a larger group | AI-run vetting at volume plus employer-of-record payroll |
| Pricing model | Collaborative team model or managed delivery; rates on request | Fixed monthly rate per engineer by seniority; one-week risk-free test; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Databricks, Spark | Python, PyTorch, LangChain |
| Industries served | Manufacturing, Automotive, Retail, Aviation | AI research labs, Startups, Software & SaaS |
Addepto vs micro1: overview
Addepto
Addepto has worked on AI and data in Warsaw since 2017, with a strong client base in industrial and automotive companies. KMS Technology, an Atlanta engineering firm backed by Sunstone Partners, acquired it in December 2025. Its collaborative cooperation model puts Addepto engineers alongside the client's own team, and the company has said publicly it is not a body-leasing firm. After the deal, its CEO said 97% of the team are AI engineers.
micro1
micro1 was founded in 2022 by Ali Ansari and built from the start around an AI recruiter, called Zara, that interviews and screens applicants. The company acts as employer of record for the engineers it places, offers full-time hires and managed teams, and lets you test any engineer for one week at no risk. Rates are fixed by seniority. Its growth has come increasingly from supplying human data and experts to AI labs, and Reuters reported a Series A at a $500 million valuation in 2025.
Services and capabilities: Addepto vs micro1
| Capability | Addepto | micro1 |
|---|---|---|
| LLM / GenAI engineers | ✓ | ✓ |
| AI agent development | ✗ | ✗ |
| MLOps & deployment | ✗ | ✗ |
| Computer vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Data engineering | ✓ | ✗ |
| Fractional / part-time experts | ✗ | ✗ |
| Trial before commitment | ✗ | ✓ |
| Forward-deployed engineers | ✗ | ✗ |
| Access to a wider AI talent network | ✗ | ✓ |
Tech stack comparison: Addepto vs micro1
| Framework / platform | Addepto | micro1 |
|---|---|---|
| PyTorch | N/A | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | N/A | N/A |
| Databricks | ✓ | N/A |
| MLflow | N/A | N/A |
Pricing comparison: Addepto vs micro1
| Criterion | Addepto | micro1 |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Embedded team, Project delivery | Dedicated engineers, Trial sprint, Embedded team |
| 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, Retail | AI research labs, Startups, Software & SaaS |
| Best use cases | Adding Databricks engineers to a manufacturer's data team, Building a GenAI assistant for automotive service documents | Hiring two remote LLM developers for a startup, Staffing a large coding-evaluation project for an AI lab |
| Typical project type | Embedded team | Dedicated engineers |
Addepto vs micro1: pros and cons
| Addepto | |
|---|---|
| + | Nearly the whole team is AI engineers, according to its CEO |
| + | Industrial and automotive client experience |
| + | KMS ownership adds broader engineering capacity behind it |
| - | Acquired by KMS Technology in December 2025; ownership changes can bring new contract terms |
| - | Prefers joint delivery to straight staff placement |
| - | Team size estimates range from 8 to 99 |
| micro1 | |
|---|---|
| + | One-week test before committing |
| + | Handles contracts and payroll as employer of record |
| + | Says it hired 60 competitive programmers for an AI lab in three weeks |
| - | AI interviews check skills, but human judgment of team fit is lighter |
| - | Its growth is tilting toward AI-lab data work over product engineering |
| - | Headquarters and headcount differ across directories |
Who should choose Addepto?
A typical fit: adding Databricks engineers to a manufacturer's data team.
AI-heavy team with manufacturing domain experience, now backed by a larger group. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Automotive, Retail, Aviation.
Who should choose micro1?
A typical fit: hiring two remote LLM developers for a startup.
AI-run vetting at volume plus employer-of-record payroll. Minimum engagement is not publicly disclosed. Works best with clients in AI research labs, Startups, Software & SaaS.
Decision matrix: Addepto vs micro1
| Your situation | Recommended choice |
|---|---|
| You need one AI specialist part-time | Neither advertises part-time experts; ask about reduced hours |
| You need several engineers working as one team | Both; Addepto rates higher overall |
| You want to test an engineer before committing | micro1 |
| Your budget is at the lower end | Compare: Addepto (Not published) vs micro1 (Not published) |
| You need engineers deployed inside your organization | Both; Addepto rates higher overall |
| You need specialist depth in a specific vertical | Addepto |
Use case fit: Addepto vs micro1
| Use case | Addepto fit | micro1 fit | Winner |
|---|---|---|---|
| Adding Databricks engineers to a manufacturer's data team | Strong | Limited | Addepto |
| Building a GenAI assistant for automotive service documents | Strong | Limited | Addepto |
| Hiring two remote LLM developers for a startup | Limited | Strong | micro1 |
| Staffing a large coding-evaluation project for an AI lab | Limited | Strong | micro1 |
Verdict: Addepto vs micro1
Addepto (3.9/5) is the stronger overall choice for most AI-Native Staff Augmentation projects. AI-heavy team with manufacturing domain experience, now backed by a larger group.
micro1 (3.8/5) is worth a look if you need staffing a large coding-evaluation project for an AI lab. If your situation matches that, micro1 is a competitive option.
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Addepto vs micro1 FAQ
Is Addepto better than micro1?
Addepto (3.9/5) scores higher overall, but "better" depends on your use case. Addepto's strongest advantage: nearly the whole team is AI engineers, according to its CEO. micro1's strongest advantage: one-week test before committing.
How do Addepto and micro1 differ in pricing?
Addepto uses collaborative team model or managed delivery; rates on request pricing. micro1 uses fixed monthly rate per engineer by seniority; one-week risk-free test; 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: AI-heavy team with manufacturing domain experience, now backed by a larger group. micro1's primary differentiator is: AI-run vetting at volume plus employer-of-record payroll. They also differ in team size (50–99 (directory estimate) vs Staff not confirmed; 3,000+ vetted engineers (per company)), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Automotive vs AI research labs, Startups).
Verify all details directly with each company before making a decision.