Fusemachines vs Addepto: full comparison for 2026
Quick verdict
Fusemachines (4.0/5) edges ahead of Addepto (4.0/5) overall. Fusemachines is the better choice for cost-conscious companies that want mid-level ML engineers from a publicly listed supplier. 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.
Fusemachines vs Addepto: head-to-head summary
| Criterion | Fusemachines | Addepto |
|---|---|---|
| Founded | 2013 | 2017 |
| HQ | New York, USA | Warsaw, Poland |
| Team size | 250–500 | 50–249 |
| Rating | 4.0 / 5 | 4.0 / 5 |
| Primary differentiator | Its own AI education programs feed an employed bench in emerging markets | Data and ML engineers with industrial and automotive client history |
| Pricing model | Monthly per engineer or team; projects quoted separately; rates on request | Monthly per engineer or project fee; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, Databricks, Spark |
| Industries served | Media, Financial services, Education, Retail, Healthcare | Manufacturing, Automotive, Aviation, Retail, Logistics |
Fusemachines vs Addepto: overview
Fusemachines
Fusemachines was founded in New York in 2013 to bring AI talent and education to underserved countries, and it trains and employs engineers in Nepal, the Dominican Republic and elsewhere. It began trading on the Nasdaq in October 2025 after a SPAC merger, which makes its finances public. Clients can take on its engineers as dedicated AI staff or buy its products and projects. Its training programs feed the bench, so junior and mid-level ML engineers are easier to find here than senior researchers.
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: Fusemachines vs Addepto
| Capability | Fusemachines | 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: Fusemachines vs Addepto
| Framework / platform | Fusemachines | Addepto |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | ✓ | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Fusemachines vs Addepto
| Criterion | Fusemachines | Addepto |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Dedicated team, Project delivery | Dedicated engineer, Dedicated team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Fusemachines vs Addepto
| Dimension | Fusemachines | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Media, Financial services, Education | Manufacturing, Automotive, Aviation |
| Best use cases | Adding two mid-level ML engineers for a media recommendation project, Staffing a data engineering team on a fixed budget | 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 |
Fusemachines vs Addepto: pros and cons
| Fusemachines | |
|---|---|
| + | Public listing means audited financial disclosure |
| + | Lower rates than U.S. or Western European engineers |
| + | Dominican Republic team overlaps with U.S. hours |
| - | Listed on the Nasdaq through a SPAC merger in October 2025, so its strategy may change under public-market pressure |
| - | Bench skews toward mid-level engineers |
| - | Nepal hours overlap poorly with the Americas |
| 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 Fusemachines?
A typical fit: adding two mid-level ML engineers for a media recommendation project.
Its own AI education programs feed an employed bench in emerging markets. Minimum engagement is not publicly disclosed. Works best with clients in Media, Financial services, Education, Retail, Healthcare.
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: Fusemachines 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; Fusemachines 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: Fusemachines (Not published) vs Addepto (Not published) |
| Your team works U.S. hours | Fusemachines |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
Use case fit: Fusemachines vs Addepto
| Use case | Fusemachines fit | Addepto fit | Winner |
|---|---|---|---|
| Adding two mid-level ML engineers for a media recommendation project | Strong | Strong | Both equally |
| Staffing a data engineering team on a fixed budget | 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 | Strong | Strong | Both equally |
Verdict: Fusemachines vs Addepto
Fusemachines (4.0/5) is the stronger overall choice for most AI Engineer Staffing projects. Its own AI education programs feed an employed bench in emerging markets.
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.
Related comparisons
Fusemachines vs Addepto FAQ
Is Fusemachines better than Addepto?
Fusemachines (4.0/5) scores higher overall, but "better" depends on your use case. Fusemachines's strongest advantage: public listing means audited financial disclosure. Addepto's strongest advantage: strong data engineering on Databricks and Azure.
How do Fusemachines and Addepto differ in pricing?
Fusemachines uses monthly per engineer or team; projects quoted separately; 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: Fusemachines or Addepto?
Fusemachines 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 Fusemachines and Addepto?
Fusemachines's primary differentiator is: its own AI education programs feed an employed bench in emerging markets. Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. They also differ in team size (250–500 vs 50–249), minimum engagement (Not published vs Not published), and primary industries served (Media, Financial services vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.