Index.dev vs InData Labs: full comparison for 2026
Quick verdict
Index.dev (4.5/5) edges ahead of InData Labs (4.0/5) overall. Index.dev is the better choice for startups that want their money back if the first month doesn't work. InData Labs is the stronger option for a small dedicated computer vision or NLP team rather than one person. The right choice depends on your project size, budget, and required tech stack.
Index.dev vs InData Labs: head-to-head summary
| Criterion | Index.dev | InData Labs |
|---|---|---|
| Founded | 2019 | 2014 |
| HQ | London, United Kingdom | Nicosia, Cyprus |
| Team size | 30,000+ network | 50–100 |
| Rating | 4.5 / 5 | 4.0 / 5 |
| Primary differentiator | A refundable 30-day trial on every placement, plus direct hire | Dedicated AI teams with ten years of computer vision and NLP work |
| Pricing model | Monthly rate per engineer; direct-hire fee; 30-day refundable trial; 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, LangChain | Python, PyTorch, OpenCV |
| Industries served | SaaS, Fintech, E-commerce, AI labs, Healthcare | Retail, Healthcare, Fintech, Media, Manufacturing |
Index.dev vs InData Labs: overview
Index.dev
Index.dev, legally Index Soft Limited, is a London talent platform that its job ads date to 2019. Its buying terms are the clearest of any network here: every placement carries a 30-day trial with a full refund if the match fails. You can contract one engineer, build a dedicated offshore team or hire someone directly. The main pool of more than 30,000 engineers sits in Latin America and Central and Eastern Europe, and a separate AI unit supplies Master's and PhD-level people for fine-tuning and retrieval work. Vetting runs through five stages with human reviewers.
InData Labs
InData Labs started in 2014 and is registered in Nicosia, Cyprus, with an office in Singapore and roughly 70 to 80 people. Clutch lists dedicated teams and staff augmentation as core services, and reported project sizes run from under $50,000 to over $100,000. Buyers get a team built around computer vision, NLP or generative AI rather than individual freelancers. It is an AWS partner. Monthly rates, minimums and trial terms are not published.
Services and capabilities: Index.dev vs InData Labs
| Capability | Index.dev | InData Labs |
|---|---|---|
| Full-time dedicated engineers | ✓ | ✗ |
| Part-time / fractional experts | ✗ | ✗ |
| Dedicated team | ✓ | ✓ |
| Trial before commitment | ✓ | ✗ |
| Published rates | ✗ | ✗ |
| Direct hire option | ✓ | ✗ |
| Subscription or output-based pricing | ✗ | ✗ |
| Nearshore time-zone overlap | ✓ | ✗ |
| LLM / GenAI engineers | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Computer vision | ✗ | ✓ |
| Data engineering | ✗ | ✗ |
Tech stack comparison: Index.dev vs InData Labs
| Framework / platform | Index.dev | InData Labs |
|---|---|---|
| PyTorch | ✓ | ✓ |
| TensorFlow | N/A | N/A |
| LangChain | ✓ | N/A |
| Hugging Face | ✓ | ✓ |
| OpenAI | ✓ | ✓ |
| AWS | ✓ | ✓ |
| Azure | N/A | N/A |
| Google Cloud | ✓ | N/A |
| Databricks | N/A | N/A |
| Kubernetes | N/A | N/A |
Pricing comparison: Index.dev vs InData Labs
| Criterion | Index.dev | InData Labs |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Full-time dedicated, Dedicated team, Direct hire, Trial period | Dedicated team, Project delivery |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Index.dev vs InData Labs
| Dimension | Index.dev | 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 | Trialling a Latin American LLM engineer for a month, Hiring a PhD-level specialist to fine-tune a model | Buying a three-person computer vision team for a retail app, Adding an NLP team for document processing |
| Typical project type | Full-time dedicated | Dedicated team |
Index.dev vs InData Labs: pros and cons
| Index.dev | |
|---|---|
| + | A full refund in the first 30 days lowers the cost of a bad match |
| + | Contract and direct-hire routes from one provider |
| + | Talent in both U.S.-friendly and European time zones |
| - | Engineers are network members, not employees |
| - | Acceptance-rate figures are the company's own |
| - | No published monthly rates |
| InData Labs | |
|---|---|
| + | AI-only company with long computer vision and NLP experience |
| + | Clutch shows typical project sizes |
| + | AWS partner |
| - | No single-engineer or part-time option published |
| - | Small team |
| - | Headquarters listed differently across sources |
Who should choose Index.dev?
A typical fit: trialling a Latin American LLM engineer for a month.
A refundable 30-day trial on every placement, plus direct hire. Minimum engagement is not publicly disclosed. Works best with clients in SaaS, Fintech, E-commerce, AI labs, Healthcare.
Who should choose InData Labs?
A typical fit: buying a three-person computer vision team for a retail app.
Dedicated AI teams with ten years of computer vision and NLP work. Minimum engagement is not publicly disclosed. Works best with clients in Retail, Healthcare, Fintech, Media, Manufacturing.
Decision matrix: Index.dev vs InData Labs
| Your situation | Recommended choice |
|---|---|
| You want one engineer full-time on a monthly contract | Index.dev |
| You only need a specialist a few days a week | Neither advertises part-time experts; ask about reduced hours |
| You want to test an engineer before committing | Index.dev |
| You need a rate before the first call | Neither publishes rates; ask both for a written rate card |
| Your budget is at the lower end | Compare: Index.dev (Not published) vs InData Labs (Not published) |
| You may want to hire the engineer permanently later | Index.dev |
| You want several engineers working as one team | InData Labs |
Use case fit: Index.dev vs InData Labs
| Use case | Index.dev fit | InData Labs fit | Winner |
|---|---|---|---|
| Trialling a Latin American LLM engineer for a month | Strong | Limited | Index.dev |
| Hiring a PhD-level specialist to fine-tune a model | Strong | Limited | Index.dev |
| Buying a three-person computer vision team for a retail app | Limited | Strong | InData Labs |
| Adding an NLP team for document processing | Limited | Strong | InData Labs |
Verdict: Index.dev vs InData Labs
Index.dev (4.5/5) is the stronger overall choice for most AI Staff Augmentation projects. A refundable 30-day trial on every placement, plus direct hire.
InData Labs (4.0/5) is worth a look if you need adding an NLP team for document processing. If your situation matches that, InData Labs is a competitive option.
Related comparisons
Index.dev vs InData Labs FAQ
Is Index.dev better than InData Labs?
Index.dev (4.5/5) scores higher overall, but "better" depends on your use case. Index.dev's strongest advantage: a full refund in the first 30 days lowers the cost of a bad match. InData Labs's strongest advantage: AI-only company with long computer vision and NLP experience.
How do Index.dev and InData Labs differ in pricing?
Index.dev uses monthly rate per engineer; direct-hire fee; 30-day refundable trial; 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: Index.dev 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 provider before shortlisting.
What are the main differences between Index.dev and InData Labs?
Index.dev's primary differentiator is: a refundable 30-day trial on every placement, plus direct hire. InData Labs's primary differentiator is: dedicated AI teams with ten years of computer vision and NLP work. They also differ in team size (30,000+ network 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 provider before making a decision.