Fusemachines
Nasdaq-listed AI company that trains its own engineers and deploys them with clients
What is 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.
Fusemachines works primarily with clients in Financial services, Media, Retail, Healthcare sectors. Its primary differentiator is: Its own AI education program feeds the engineering bench.
Fusemachines tech stack and services
| Service area |
|---|
| ML Engineers |
| Data Engineering |
| AI Agent Developers |
| Forward-Deployed Engineers |
| Dedicated Teams |
Fusemachines pricing
Short answer: Fusemachines uses a squad or per-engineer billing for services; product licences priced separately; rates on request pricing approach. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Embedded team | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated engineers | Variable; depends on team size | Large programmes or team augmentation |
| Project delivery | Variable; depends on team size | Large programmes or team augmentation |
Fusemachines pros and cons
| Advantages | Things to consider |
|---|---|
| +Public-company reporting means audited financials, which few staffing vendors offer | -Ownership changed through the October 2025 SPAC listing, and public-market pressure may shift priorities toward its products |
| +Engineers trained through its own fellowship arrive with a shared baseline | -Product sales and staffing share the same engineers, so availability can tighten |
| +Forward-deployed engineers can tune the company's own agent products in your environment | -Nepal time zones offer limited overlap with the Americas |
| +Offshore delivery from Nepal keeps costs below U.S. hiring |
Fusemachines vs alternatives
How Fusemachines compares to the other top AI-Native Staff Augmentation companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Quantiphi | Enterprises that need several AI specialists at once... | A multi-thousand-person AI and data bench with a named staffing program run with AWS | 4.6 | Full comparison |
| Tensorway | Product teams that want senior AI engineers inside... | Senior AI engineers run the screening, and knowledge transfer to in-house staff is part of every engagement | 4.5 | Full comparison |
| deepsense.ai | Long MLOps or computer-vision engagements that need senior... | A decade of ML-only delivery, with multi-year augmentation clients on record | 4.4 | Full comparison |
| InData Labs | Buyers who want an R&D-minded data science team... | Research-led data science with a dedicated-team option | 4.2 | Full comparison |
| Sigmoid | CPG and retail data teams that need ML... | Requirement-by-requirement split between project work and monthly staff augmentation | 4.2 | Full comparison |
| Data Science UA | Companies building a Ukrainian AI team they will... | Recruiting from Ukraine's largest AI community, with managed teams as an option | 4.1 | Full comparison |
| Algoscale | Budget-conscious teams that need data engineers and ML... | Data consulting experience bundled into staff augmentation, plus a free trial | 4.1 | Full comparison |
| Kanerika | Enterprises modernizing data platforms that want onshore, nearshore... | Three delivery models under one contract, from Austin, Argentina and India | 4.0 | Full comparison |
| Vstorm | Teams whose agent prototype works in a demo... | Senior agent engineers who join an existing team to fix reliability and integration | 4.0 | Full comparison |
| Fuzzy Labs | UK data science teams, including public sector, that... | Open-source MLOps specialists with security-cleared engineers for government work | 4.0 | Full comparison |
| Tribe AI | Companies that want senior AI engineers and product... | A curated network of senior AI practitioners deployed inside the client's organization | 4.0 | Full comparison |
| Addepto | Industrial and automotive companies adding AI and data... | AI-heavy team with manufacturing domain experience, now backed by a larger group | 3.9 | Full comparison |
| Neurons Lab | Banks and insurers that need agentic AI engineers... | Financial-services AI with AWS GenAI competency and forward-deployed engineers | 3.9 | Full comparison |
| Merantix Momentum | German industrial companies that want an outside ML... | Operates as a company's ML function, backed by the Merantix AI ecosystem | 3.9 | Full comparison |
| Sciforce | Healthcare and scientific data projects that need NLP... | Medical and scientific data experience in a small AI-first firm | 3.9 | Full comparison |
| Pento | U.S. startups and mid-market firms that want nearshore... | AI-only engineering from Uruguay with full U.S. working-hour overlap | 3.9 | Full comparison |
| DataToBiz | Analytics teams that need BI and data science... | Fast placement of data and BI specialists with AI skills | 3.8 | Full comparison |
| Sigmoidal | U.S. companies that want a small ML team... | Data-centric ML specialists with a staff augmentation model for long engagements | 3.8 | Full comparison |
| Omdena | Startups and mission-driven organizations that want to see... | Challenge-based vetting where engineers solve your real problem before you hire | 3.8 | Full comparison |
| micro1 | Startups that want vetted remote AI developers quickly,... | AI-run vetting at volume plus employer-of-record payroll | 3.8 | Full comparison |
| Dataroots | Benelux enterprises that need ML and data engineers... | Benelux data platform specialists backed by Talan's wider consulting group | 3.8 | Full comparison |
| BroutonLab | Startups that need a PhD-level data scientist part-time... | Fractional deep learning experts at a published hourly rate | 3.7 | Full comparison |
| Experfy | Enterprises that want a private, pre-vetted pool of... | Private talent clouds with expert vetting and employer-of-record cover | 3.7 | Full comparison |
| Dataforest | Companies that need data engineers who can also... | Data engineering depth with AI agent work on top | 3.7 | Full comparison |
| BotsCrew | Companies adding chatbot or voice-agent engineers to a... | Nearly a decade of conversational AI work, now with U.S. ownership | 3.7 | Full comparison |
| Brainpool AI | Buyers who need a rare academic AI specialist... | Academic-heavy expert network across 23 countries | 3.6 | Full comparison |
| Mercor | AI labs and companies that need evaluation or... | AI interviewing that can screen very large candidate pools quickly | 3.6 | Full comparison |
| Data Pilot | Small budgets that need a data and ML... | Low-cost data and ML team that can also manage the developers it sources | 3.6 | Full comparison |
Fusemachines FAQ
What is Fusemachines?
Nasdaq-listed AI company that trains its own engineers and deploys them with clients
How much does Fusemachines charge?
Fusemachines uses squad or per-engineer billing for services; product licences priced separately; rates on request pricing. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does Fusemachines use?
Fusemachines works with Python, PyTorch, TensorFlow, LangChain, OpenAI, AWS, Azure, Databricks, Snowflake. Primary industries served include Financial services, Media, Retail, Healthcare.
Is Fusemachines right for enterprise?
Mid-market and enterprise buyers who want AI engineers plus a product platform from one vendor. Not confirmed in sources reviewed (Nasdaq filer; see SEC reports) team size. Key consideration: Ownership changed through the October 2025 SPAC listing, and public-market pressure may shift priorities toward its products.
What are the best Fusemachines alternatives?
The best alternatives to Fusemachines depend on your use case. Top options are:
- Quantiphi: a multi-thousand-person ai and data bench with a named staffing program run with aws
- Tensorway: senior ai engineers run the screening, and knowledge transfer to in-house staff is part of every engagement
- deepsense.ai: a decade of ml-only delivery, with multi-year augmentation clients on record
Compare Fusemachines with other AI-Native Staff Augmentation companies
Verify all details directly with Fusemachines before making a decision.