Fusemachines vs Addepto: full comparison for 2026
Quick verdict
Fusemachines (4.3/5) edges ahead of Addepto (3.9/5) overall. Fusemachines is the better choice for mid-market and enterprise buyers who want AI engineers plus a product platform from one vendor. Addepto is the stronger option for industrial and automotive companies adding AI and data engineers to an internal team. 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, New York, USA | Warsaw, Poland |
| Team size | Not confirmed in sources reviewed (Nasdaq filer; see SEC reports) | 50–99 (directory estimate) |
| Rating | 4.3 / 5 | 3.9 / 5 |
| Primary differentiator | Its own AI education program feeds the engineering bench | AI-heavy team with manufacturing domain experience, now backed by a larger group |
| Pricing model | Squad or per-engineer billing for services; product licences priced separately; rates on request | Collaborative team model or managed delivery; rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Databricks, Spark |
| Industries served | Financial services, Media, Retail, Healthcare | Manufacturing, Automotive, Retail, Aviation |
Fusemachines vs Addepto: overview
Fusemachines
Fusemachines was founded in New York in 2013 by Sameer Maskey, a Columbia adjunct professor, around a simple idea: train AI engineers in places big tech ignores, then put them to work for enterprise clients. Its AI Fellowship program has trained engineers in Nepal, the Dominican Republic and Rwanda. The company went public on the Nasdaq Global Market (ticker FUSE) on October 23, 2025, through a merger with the SPAC CSLM Acquisition Corp. Today it sells its own AI Studio and agent products alongside forward-deployed engineers and small squads of data and ML specialists who work inside client organizations.
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.
Services and capabilities: Fusemachines vs Addepto
| Capability | Fusemachines | Addepto |
|---|---|---|
| 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: Fusemachines vs Addepto
| Framework / platform | Fusemachines | Addepto |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | N/A | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | ✓ | ✓ |
| MLflow | N/A | N/A |
Pricing comparison: Fusemachines vs Addepto
| Criterion | Fusemachines | Addepto |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Embedded team, Dedicated engineers, Project delivery | Embedded 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 | Financial services, Media, Retail | Manufacturing, Automotive, Retail |
| Best use cases | Placing a data engineering squad inside a mid-market retailer, Customizing agent products for a financial services back office | Adding Databricks engineers to a manufacturer's data team, Building a GenAI assistant for automotive service documents |
| Typical project type | Embedded team | Embedded team |
Fusemachines vs Addepto: pros and cons
| Fusemachines | |
|---|---|
| + | Public-company reporting means audited financials, which few staffing vendors offer |
| + | Engineers trained through its own fellowship arrive with a shared baseline |
| + | Forward-deployed engineers can tune the company's own agent products in your environment |
| + | Offshore delivery from Nepal keeps costs below U.S. hiring |
| - | Ownership changed through the October 2025 SPAC listing, and public-market pressure may shift priorities toward its products |
| - | Product sales and staffing share the same engineers, so availability can tighten |
| - | Nepal time zones offer limited overlap with the Americas |
| 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 |
Who should choose Fusemachines?
A typical fit: placing a data engineering squad inside a mid-market retailer.
Its own AI education program feeds the engineering bench. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Media, Retail, Healthcare.
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.
Decision matrix: Fusemachines vs Addepto
| 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; 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) |
| You need engineers deployed inside your organization | Both; Fusemachines rates higher overall |
| You need specialist depth in a specific vertical | Fusemachines |
Use case fit: Fusemachines vs Addepto
| Use case | Fusemachines fit | Addepto fit | Winner |
|---|---|---|---|
| Placing a data engineering squad inside a mid-market retailer | Strong | Limited | Fusemachines |
| Customizing agent products for a financial services back office | Strong | Limited | Fusemachines |
| Adding Databricks engineers to a manufacturer's data team | Limited | Strong | Addepto |
| Building a GenAI assistant for automotive service documents | Limited | Strong | Addepto |
Verdict: Fusemachines vs Addepto
Fusemachines (4.3/5) is the stronger overall choice for most AI-Native Staff Augmentation projects. Its own AI education program feeds the engineering bench.
Addepto (3.9/5) is worth a look if you need building a GenAI assistant for automotive service documents. If your situation matches that, Addepto is a competitive option.
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Fusemachines vs Addepto FAQ
Is Fusemachines better than Addepto?
Fusemachines (4.3/5) scores higher overall, but "better" depends on your use case. Fusemachines's strongest advantage: public-company reporting means audited financials, which few staffing vendors offer. Addepto's strongest advantage: nearly the whole team is AI engineers, according to its CEO.
How do Fusemachines and Addepto differ in pricing?
Fusemachines uses squad or per-engineer billing for services; product licences priced separately; rates on request pricing. Addepto uses collaborative team model or managed delivery; 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?
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 Fusemachines and Addepto?
Fusemachines's primary differentiator is: its own AI education program feeds the engineering bench. Addepto's primary differentiator is: AI-heavy team with manufacturing domain experience, now backed by a larger group. They also differ in team size (Not confirmed in sources reviewed (Nasdaq filer; see SEC reports) vs 50–99 (directory estimate)), minimum engagement (Not published vs Not published), and primary industries served (Financial services, Media vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.