Tensorway vs Addepto: full comparison for 2026
Quick verdict
Tensorway (4.5/5) edges ahead of Addepto (3.9/5) overall. Tensorway is the better choice for product teams that want senior AI engineers inside their own workflow and want the know-how to stay. 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.
Tensorway vs Addepto: head-to-head summary
| Criterion | Tensorway | Addepto |
|---|---|---|
| Founded | 2019 | 2017 |
| HQ | Alicante, Spain | Warsaw, Poland |
| Team size | 50–249 | 50–99 (directory estimate) |
| Rating | 4.5 / 5 | 3.9 / 5 |
| Primary differentiator | Senior AI engineers run the screening, and knowledge transfer to in-house staff is part of every engagement | AI-heavy team with manufacturing domain experience, now backed by a larger group |
| Pricing model | Monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card on request | Collaborative team model or managed delivery; rates on request |
| Min. engagement | Not disclosed | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, Databricks, Spark |
| Industries served | Financial services, SaaS, Logistics, Healthcare, Retail & e-commerce, Manufacturing | Manufacturing, Automotive, Retail, Aviation |
Tensorway vs Addepto: overview
Tensorway
Tensorway was set up in Alicante, Spain in 2019 to do one thing: AI engineering. Its delivery practice draws on more than two decades of software engineering. Its staff-augmentation service supplies ML engineers, AI agent developers, data engineers and other specialists who work inside the client's own Slack, Jira and repositories. Most engagements start as a squad of two to five people and change shape as the work moves from research to production, with a part-time fractional expert as an option when a full seat is too much. The company's case studies include a multi-billion-euro Swedish private equity fund, where an AI-agent system reportedly cut deal-sourcing time by 80% and screens more than 5,000 opportunities in hours (per company website; independently unverifiable).
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: Tensorway vs Addepto
| Capability | Tensorway | 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: Tensorway vs Addepto
| Framework / platform | Tensorway | Addepto |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | N/A | ✓ |
| MLflow | N/A | N/A |
Pricing comparison: Tensorway vs Addepto
| Criterion | Tensorway | Addepto |
|---|---|---|
| Minimum engagement | Not disclosed | Not published |
| Engagement models | Dedicated engineers, Fractional experts, Trial sprint | Embedded team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Tensorway vs Addepto
| Dimension | Tensorway | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, SaaS, Logistics | Manufacturing, Automotive, Retail |
| Best use cases | Building an AI-agent system for deal sourcing at an investment firm, Adding a fractional MLOps expert to cut inference costs | Adding Databricks engineers to a manufacturer's data team, Building a GenAI assistant for automotive service documents |
| Typical project type | Dedicated engineers | Embedded team |
Tensorway vs Addepto: pros and cons
| Tensorway | |
|---|---|
| + | Candidates pass a code review, a practical task in their specialty and a communication check, all run by senior AI engineers |
| + | A two-week trial sprint lets you judge real output before the monthly commitment starts |
| + | Fractional experts cover narrow needs, such as a few days a week of fine-tuning or GPU cost work |
| + | Code, documentation and trained models stay in your repositories, and handover to in-house staff is planned from the start |
| + | Shortlist in days and first engineer in one to two weeks (per company website; independently unverifiable) |
| - | No published rates, so budgeting needs a call |
| - | The bench is far smaller than Quantiphi's, so a request for ten engineers at once would stretch it |
| - | Time-zone overlap is agreed per engagement; there is no fixed nearshore promise |
| - | Staffs AI and ML roles only, so general web or mobile developers have to come from elsewhere |
| 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 Tensorway?
A typical fit: building an AI-agent system for deal sourcing at an investment firm.
Senior AI engineers run the screening, and knowledge transfer to in-house staff is part of every engagement. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, SaaS, Logistics, Healthcare, Retail & e-commerce, Manufacturing.
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: Tensorway vs Addepto
| Your situation | Recommended choice |
|---|---|
| You need one AI specialist part-time | Tensorway |
| You need several engineers working as one team | Both; Tensorway rates higher overall |
| You want to test an engineer before committing | Tensorway |
| Your budget is at the lower end | Compare: Tensorway (Not disclosed) vs Addepto (Not published) |
| You need engineers deployed inside your organization | Addepto |
| You need specialist depth in a specific vertical | Tensorway |
Use case fit: Tensorway vs Addepto
| Use case | Tensorway fit | Addepto fit | Winner |
|---|---|---|---|
| Building an AI-agent system for deal sourcing at an investment firm | Strong | Strong | Both equally |
| Adding a fractional MLOps expert to cut inference costs | Strong | Strong | Both equally |
| Adding Databricks engineers to a manufacturer's data team | Strong | Strong | Both equally |
| Building a GenAI assistant for automotive service documents | Strong | Strong | Both equally |
Verdict: Tensorway vs Addepto
Tensorway (4.5/5) is the stronger overall choice for most AI-Native Staff Augmentation projects. Senior AI engineers run the screening, and knowledge transfer to in-house staff is part of every engagement.
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.
Related comparisons
Tensorway vs Addepto FAQ
Is Tensorway better than Addepto?
Tensorway (4.5/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: candidates pass a code review, a practical task in their specialty and a communication check, all run by senior AI engineers. Addepto's strongest advantage: nearly the whole team is AI engineers, according to its CEO.
How do Tensorway and Addepto differ in pricing?
Tensorway uses monthly rate for full-time dedicated engineers; hourly or weekly billing for part-time fractional experts; two-week trial sprint; rate card 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: Tensorway or Addepto?
Tensorway 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 Tensorway and Addepto?
Tensorway's primary differentiator is: senior AI engineers run the screening, and knowledge transfer to in-house staff is part of every engagement. Addepto's primary differentiator is: AI-heavy team with manufacturing domain experience, now backed by a larger group. They also differ in team size (50–249 vs 50–99 (directory estimate)), minimum engagement (Not disclosed vs Not published), and primary industries served (Financial services, SaaS vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.