InData Labs vs Addepto: full comparison for 2026
Quick verdict
InData Labs (4.4/5) edges ahead of Addepto (4.0/5) overall. InData Labs is the better choice for product teams that need a computer-vision or NLP engineer with shipped work in that exact area. 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.
InData Labs vs Addepto: head-to-head summary
| Criterion | InData Labs | Addepto |
|---|---|---|
| Founded | 2014 | 2017 |
| HQ | Nicosia, Cyprus | Warsaw, Poland |
| Team size | 50–100 | 50–249 |
| Rating | 4.4 / 5 | 4.0 / 5 |
| Primary differentiator | Ten years of computer-vision and NLP delivery in an AI-only company | Data and ML engineers with industrial and automotive client history |
| Pricing model | Dedicated team billed monthly; projects from under $50,000 to over $100,000 (Clutch); 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 | Retail, Healthcare, Fintech, Media, Manufacturing | Manufacturing, Automotive, Aviation, Retail, Logistics |
InData Labs vs Addepto: overview
InData Labs
InData Labs has worked on data science and AI since 2014 and is registered in Nicosia, Cyprus, with an office in Singapore. Clutch lists dedicated teams and staff augmentation among its core services, next to generative AI, computer vision and predictive analytics, and the company reports more than 150 delivered projects. It is an AWS partner. Directories put the team at roughly 70 to 80 people, all working on AI and data, so the people who interview candidates are practitioners in the same field. Computer vision and natural language processing are where its case studies are strongest.
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: InData Labs vs Addepto
| Capability | InData Labs | 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: InData Labs vs Addepto
| Framework / platform | InData Labs | Addepto |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | N/A |
| LangChain | N/A | N/A |
| Hugging Face | ✓ | N/A |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Google Cloud | N/A | N/A |
| Databricks | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: InData Labs vs Addepto
| Criterion | InData Labs | 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: InData Labs vs Addepto
| Dimension | InData Labs | Addepto |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Retail, Healthcare, Fintech | Manufacturing, Automotive, Aviation |
| Best use cases | Adding a computer-vision engineer to a retail shelf-analytics product, Staffing an NLP specialist for document classification | 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 |
InData Labs vs Addepto: pros and cons
| InData Labs | |
|---|---|
| + | Computer vision and NLP are core skills, not side offerings |
| + | Every engineer works in AI or data, so candidates are vetted by peers |
| + | AWS partner status helps on SageMaker-heavy projects |
| - | Small, with directory counts between 67 and 80 people |
| - | Sources disagree on the headquarters (Cyprus or Miami) |
| - | No published hourly rate |
| 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 InData Labs?
A typical fit: adding a computer-vision engineer to a retail shelf-analytics product.
Ten years of computer-vision and NLP delivery in an AI-only company. Minimum engagement is not publicly disclosed. Works best with clients in Retail, Healthcare, Fintech, Media, Manufacturing.
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: InData Labs vs Addepto
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | InData Labs |
| 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 | Both; InData Labs 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: InData Labs (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: InData Labs vs Addepto
| Use case | InData Labs fit | Addepto fit | Winner |
|---|---|---|---|
| Adding a computer-vision engineer to a retail shelf-analytics product | Strong | Strong | Both equally |
| Staffing an NLP specialist for document classification | 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: InData Labs vs Addepto
InData Labs (4.4/5) is the stronger overall choice for most AI Engineer Staffing projects. Ten years of computer-vision and NLP delivery in an AI-only company.
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.
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InData Labs vs Addepto FAQ
Is InData Labs better than Addepto?
InData Labs (4.4/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: computer vision and NLP are core skills, not side offerings. Addepto's strongest advantage: strong data engineering on Databricks and Azure.
How do InData Labs and Addepto differ in pricing?
InData Labs uses dedicated team billed monthly; projects from under $50,000 to over $100,000 (clutch); 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: InData Labs 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 InData Labs and Addepto?
InData Labs's primary differentiator is: ten years of computer-vision and NLP delivery in an AI-only company. Addepto's primary differentiator is: data and ML engineers with industrial and automotive client history. They also differ in team size (50–100 vs 50–249), minimum engagement (Not published vs Not published), and primary industries served (Retail, Healthcare vs Manufacturing, Automotive).
Verify all details directly with each company before making a decision.