Proxify vs InData Labs: full comparison for 2026
Quick verdict
Proxify (4.4/5) edges ahead of InData Labs (4.4/5) overall. Proxify is the better choice for european companies that want a vetted ML or data engineer on European working hours. InData Labs is the stronger option for product teams that need a computer-vision or NLP engineer with shipped work in that exact area. The right choice depends on your project size, budget, and required tech stack.
Proxify vs InData Labs: head-to-head summary
| Criterion | Proxify | InData Labs |
|---|---|---|
| Founded | 2018 | 2014 |
| HQ | Stockholm, Sweden | Nicosia, Cyprus |
| Team size | 5,000+ network members | 50–100 |
| Rating | 4.4 / 5 | 4.4 / 5 |
| Primary differentiator | Senior-engineer interviews with live coding after an automated skills test | Ten years of computer-vision and NLP delivery in an AI-only company |
| Pricing model | Hourly rate per developer billed monthly; full-time or part-time; rates on request | Dedicated team billed monthly; projects from under $50,000 to over $100,000 (Clutch); rates on request |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, PyTorch, TensorFlow | Python, PyTorch, TensorFlow |
| Industries served | SaaS, Fintech, E-commerce, Media, Healthcare | Retail, Healthcare, Fintech, Media, Manufacturing |
Proxify vs InData Labs: overview
Proxify
Proxify was founded in Stockholm in 2018 (one of its own pages says 2019) and matches companies with vetted developers across web, data, AI and DevOps. Candidates take Codility-based skills tests, then sit in-depth technical interviews with Proxify's senior engineers that include live coding and practical problems. The company quotes an acceptance rate of 1–3%, though the figure varies from page to page. Its network covers more than 5,000 professionals in over 90 countries, and it appeared on the Financial Times 1,000 list in 2025. Matching uses in-house AI tools alongside its hiring team.
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.
Services and capabilities: Proxify vs InData Labs
| Capability | Proxify | InData Labs |
|---|---|---|
| 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: Proxify vs InData Labs
| Framework / platform | Proxify | InData Labs |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| LangChain | N/A | N/A |
| Hugging Face | N/A | ✓ |
| OpenAI | N/A | ✓ |
| AWS | ✓ | ✓ |
| Azure | ✓ | N/A |
| Google Cloud | ✓ | N/A |
| Databricks | ✓ | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Proxify vs InData Labs
| Criterion | Proxify | InData Labs |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Dedicated engineer, Fractional expert, Freelance contract | Dedicated engineer, Dedicated team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Proxify vs InData Labs
| Dimension | Proxify | InData Labs |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, E-commerce | Retail, Healthcare, Fintech |
| Best use cases | Adding a data engineer to a European fintech's analytics team, Hiring a Python ML developer for a recommender system | Adding a computer-vision engineer to a retail shelf-analytics product, Staffing an NLP specialist for document classification |
| Typical project type | Dedicated engineer | Dedicated engineer |
Proxify vs InData Labs: pros and cons
| Proxify | |
|---|---|
| + | Live-coding interviews with in-house senior engineers are part of the published process |
| + | Most of the network is in European time zones, which suits teams in the EU and UK |
| + | Grew fast enough to make the Financial Times 1,000 list in 2025 |
| - | AI is one of many skill areas, and there is no AI-specific test on the record |
| - | Acceptance-rate and network-size figures differ across the company's own pages |
| - | Developers are contractors on the platform, not Proxify employees |
| 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 |
Who should choose Proxify?
A typical fit: adding a data engineer to a European fintech's analytics team.
Senior-engineer interviews with live coding after an automated skills test. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, E-commerce, Media, Healthcare.
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.
Decision matrix: Proxify vs InData Labs
| Your situation | Recommended choice |
|---|---|
| You want a working engineer, not a recruiter, to run the technical screen | Both; Proxify rates higher overall |
| You need one specialist for a few days a week | Proxify |
| You need several engineers working as one team | Both; Proxify 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: Proxify (Not published) vs InData Labs (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: Proxify vs InData Labs
| Use case | Proxify fit | InData Labs fit | Winner |
|---|---|---|---|
| Adding a data engineer to a European fintech's analytics team | Strong | Strong | Both equally |
| Hiring a Python ML developer for a recommender system | Strong | Limited | Proxify |
| Adding a computer-vision engineer to a retail shelf-analytics product | Strong | Strong | Both equally |
| Staffing an NLP specialist for document classification | Limited | Strong | InData Labs |
Verdict: Proxify vs InData Labs
Proxify (4.4/5) is the stronger overall choice for most AI Engineer Staffing projects. Senior-engineer interviews with live coding after an automated skills test.
InData Labs (4.4/5) is worth a look if you need staffing an NLP specialist for document classification. If your situation matches that, InData Labs is a competitive option.
Related comparisons
Proxify vs InData Labs FAQ
Is Proxify better than InData Labs?
Proxify (4.4/5) scores higher overall, but "better" depends on your use case. Proxify's strongest advantage: live-coding interviews with in-house senior engineers are part of the published process. InData Labs's strongest advantage: computer vision and NLP are core skills, not side offerings.
How do Proxify and InData Labs differ in pricing?
Proxify uses hourly rate per developer billed monthly; full-time or part-time; rates on request pricing. InData Labs uses dedicated team billed monthly; projects from under $50,000 to over $100,000 (clutch); 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: Proxify or InData Labs?
InData Labs 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 Proxify and InData Labs?
Proxify's primary differentiator is: senior-engineer interviews with live coding after an automated skills test. InData Labs's primary differentiator is: ten years of computer-vision and NLP delivery in an AI-only company. They also differ in team size (5,000+ network members vs 50–100), minimum engagement (Not published vs Not published), and primary industries served (SaaS, Fintech vs Retail, Healthcare).
Verify all details directly with each company before making a decision.