deepsense.ai vs Addepto: full comparison for 2026
Quick verdict
deepsense.ai (4.4/5) edges ahead of Addepto (3.9/5) overall. deepsense.ai is the better choice for long MLOps or computer-vision engagements that need senior European engineers. 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.
deepsense.ai vs Addepto: head-to-head summary
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Founded | 2014 | 2017 |
| HQ | Warsaw, Poland | Warsaw, Poland |
| Team size | 100+ engineers and data scientists (per company) | 50–99 (directory estimate) |
| Rating | 4.4 / 5 | 3.9 / 5 |
| Primary differentiator | A decade of ML-only delivery, with multi-year augmentation clients on record | AI-heavy team with manufacturing domain experience, now backed by a larger group |
| Pricing model | Time-and-materials per engineer after a free assessment; 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 | Software & technology, Retail, Healthcare, Manufacturing | Manufacturing, Automotive, Retail, Aviation |
deepsense.ai vs Addepto: overview
deepsense.ai
deepsense.ai started in Warsaw in 2014 and has spent its whole history on machine learning, which shows in the depth of its MLOps and computer-vision work. It sells team augmentation as a named service and says more than 100 data scientists and engineers are available to join client teams. One client describes a dedicated team of deepsense.ai consultants working inside its MLOps function for three years, and DocPlanner credits an advisory engagement with a thorough knowledge transfer to its in-house AI team. A free assessment and quote are offered before any contract.
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: deepsense.ai vs Addepto
| Capability | deepsense.ai | 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: deepsense.ai vs Addepto
| Framework / platform | deepsense.ai | Addepto |
|---|---|---|
| PyTorch | ✓ | N/A |
| TensorFlow | ✓ | N/A |
| LangChain | ✓ | ✓ |
| Hugging Face | ✓ | N/A |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | ✓ |
| MLflow | ✓ | N/A |
Pricing comparison: deepsense.ai vs Addepto
| Criterion | deepsense.ai | Addepto |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineers, Embedded team, Project delivery | Embedded 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 | Software & technology, Retail, Healthcare | Manufacturing, Automotive, Retail |
| Best use cases | Embedding an MLOps team for a multi-year platform build, Adding computer-vision engineers to a retail analytics product | Adding Databricks engineers to a manufacturer's data team, Building a GenAI assistant for automotive service documents |
| Typical project type | Dedicated engineers | Embedded team |
deepsense.ai vs Addepto: pros and cons
| deepsense.ai | |
|---|---|
| + | Team augmentation is a published service with its own page, which says a lot about how often they do it |
| + | Clutch reviewers describe quick onboarding into existing codebases |
| + | Strong MLOps record, including a three-year embedded engagement |
| + | Free assessment before you commit |
| - | About 100 engineers is plenty for a squad but thin for a large program |
| - | Rates are not published; one Clutch review cites roughly $100,000 for a single engagement |
| - | Warsaw hours give only a short overlap with U.S. West Coast teams |
| 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 deepsense.ai?
A typical fit: embedding an MLOps team for a multi-year platform build.
A decade of ML-only delivery, with multi-year augmentation clients on record. Minimum engagement is not publicly disclosed. Works best with clients in Software & technology, Retail, Healthcare, 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: deepsense.ai 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; deepsense.ai 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: deepsense.ai (Not published) vs Addepto (Not published) |
| You need engineers deployed inside your organization | Both; deepsense.ai rates higher overall |
| You need specialist depth in a specific vertical | deepsense.ai |
Use case fit: deepsense.ai vs Addepto
| Use case | deepsense.ai fit | Addepto fit | Winner |
|---|---|---|---|
| Embedding an MLOps team for a multi-year platform build | Strong | Limited | deepsense.ai |
| Adding computer-vision engineers to a retail analytics product | 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 | Limited | Strong | Addepto |
Verdict: deepsense.ai vs Addepto
deepsense.ai (4.4/5) is the stronger overall choice for most AI-Native Staff Augmentation projects. A decade of ML-only delivery, with multi-year augmentation clients on record.
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
deepsense.ai vs Addepto FAQ
Is deepsense.ai better than Addepto?
deepsense.ai (4.4/5) scores higher overall, but "better" depends on your use case. deepsense.ai's strongest advantage: team augmentation is a published service with its own page, which says a lot about how often they do it. Addepto's strongest advantage: nearly the whole team is AI engineers, according to its CEO.
How do deepsense.ai and Addepto differ in pricing?
deepsense.ai uses time-and-materials per engineer after a free assessment; 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: deepsense.ai 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 deepsense.ai and Addepto?
deepsense.ai's primary differentiator is: a decade of ML-only delivery, with multi-year augmentation clients on record. Addepto's primary differentiator is: AI-heavy team with manufacturing domain experience, now backed by a larger group. They also differ in team size (100+ engineers and data scientists (per company) vs 50–99 (directory estimate)), minimum engagement (Not published vs Not published), and primary industries served (Software & technology, Retail vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.