deepsense.ai vs Addepto: full comparison for 2026
Quick verdict
deepsense.ai (4.6/5) edges ahead of Addepto (4.0/5) overall. deepsense.ai is the better choice for teams that need a senior ML researcher who can also put models into production. 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.
deepsense.ai vs Addepto: head-to-head summary
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Founded | 2014 | 2017 |
| HQ | Warsaw, Poland | Warsaw, Poland |
| Team size | 100–200 | 50–249 |
| Rating | 4.6 / 5 | 4.0 / 5 |
| Primary differentiator | A research-heavy bench of about 120 employed AI specialists with ten years of production work | Data and ML engineers with industrial and automotive client history |
| Pricing model | Team extension billed monthly per engineer; 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, PyTorch, TensorFlow | Python, Databricks, Spark |
| Industries served | Manufacturing, Retail, Healthcare, Financial services, Technology | Manufacturing, Automotive, Aviation, Retail, Logistics |
deepsense.ai vs Addepto: overview
deepsense.ai
deepsense.ai has done AI work out of Warsaw since 2014, and its job listings describe a team of about 120 AI specialists who have delivered more than 200 commercial and research projects. Most of that team is employed directly, which matters if you want the same engineer for a year. The company sells team extension alongside its consulting work, and its recruiting ads ask for five or more years of production ML experience for senior roles. Strengths cluster around LLM and RAG systems, computer vision, defect detection and models that run on edge devices.
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: deepsense.ai vs Addepto
| Capability | deepsense.ai | 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: deepsense.ai vs Addepto
| Framework / platform | deepsense.ai | Addepto |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | ✓ | N/A |
Pricing comparison: deepsense.ai vs Addepto
| Criterion | deepsense.ai | 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: deepsense.ai vs Addepto
| Dimension | deepsense.ai | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Manufacturing, Retail, Healthcare | Manufacturing, Automotive, Aviation |
| Best use cases | Embedding an MLOps engineer in a platform team for a long engagement, Adding a computer-vision specialist for an edge defect-detection model | 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 |
deepsense.ai vs Addepto: pros and cons
| deepsense.ai | |
|---|---|
| + | Hiring ads for senior ML roles require five or more years of production experience |
| + | Engineers are mostly employees rather than contractors, which helps continuity |
| + | Deep computer-vision and edge-deployment experience, which few staffing firms can match |
| - | About 120 people, so large or sudden requests may wait |
| - | Staff augmentation is not its headline service; consulting projects get more of its marketing |
| - | No published rates or minimums |
| 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 deepsense.ai?
A typical fit: embedding an MLOps engineer in a platform team for a long engagement.
A research-heavy bench of about 120 employed AI specialists with ten years of production work. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail, Healthcare, Financial services, Technology.
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: deepsense.ai vs Addepto
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | deepsense.ai |
| 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 | Addepto |
| 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: deepsense.ai (Not published) vs Addepto (Not published) |
| Your team works U.S. hours | Neither lists Latin American engineers; confirm overlap hours in the contract |
| You may want to hire the engineer permanently later | Neither lists direct hire; agree conversion terms up front |
Use case fit: deepsense.ai vs Addepto
| Use case | deepsense.ai fit | Addepto fit | Winner |
|---|---|---|---|
| Embedding an MLOps engineer in a platform team for a long engagement | Strong | Limited | deepsense.ai |
| Adding a computer-vision specialist for an edge defect-detection model | 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 | Limited | Strong | Addepto |
Verdict: deepsense.ai vs Addepto
deepsense.ai (4.6/5) is the stronger overall choice for most AI Engineer Staffing projects. A research-heavy bench of about 120 employed AI specialists with ten years of production work.
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
deepsense.ai vs Addepto FAQ
Is deepsense.ai better than Addepto?
deepsense.ai (4.6/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: hiring ads for senior ML roles require five or more years of production experience. Addepto's strongest advantage: strong data engineering on Databricks and Azure.
How do deepsense.ai and Addepto differ in pricing?
deepsense.ai uses team extension billed monthly per engineer; 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: deepsense.ai or Addepto?
deepsense.ai 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 deepsense.ai and Addepto?
deepsense.ai's primary differentiator is: a research-heavy bench of about 120 employed AI specialists with ten years of production work. Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. They also differ in team size (100–200 vs 50–249), minimum engagement (Not published vs Not published), and primary industries served (Manufacturing, Retail vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.