InData Labs vs Codiant: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.8/5) edges ahead of Codiant (3.6/5) overall. InData Labs is the better choice for mid-market companies needing custom production-grade ML systems with verified delivery track record and ongoing support. Codiant is the stronger option for startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Codiant: head-to-head summary
| Criterion | InData Labs | Codiant |
|---|---|---|
| Founded | 2014 | 2011 |
| HQ | Nicosia, Cyprus | Illinois, USA / India |
| Team size | 100–200 | 200–300 |
| Rating | 4.8 / 5 | 3.6 / 5 |
| Best for | Mid-market companies needing custom production-grade ML systems with verified delivery track record and ongoing support | Startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost |
| Pricing model | Fixed project, T&M, retainer | Fixed project, dedicated team, T&M |
| Min. engagement | $25K | $15K |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | FinTech, Healthcare, SaaS, Retail, Logistics, E-commerce | Healthcare, Fintech, E-commerce, SaaS, Logistics |
InData Labs vs Codiant: overview
InData Labs
InData Labs is a specialist AI and data science consultancy founded in 2014, headquartered in Nicosia, Cyprus with offices in Lithuania and the United States. The firm builds production-grade machine learning systems across predictive analytics, computer vision, NLP, and recommendation engine use cases. With a 4.9/5 rating on Clutch across 18 verified reviews, InData Labs has established a reputation for delivery accountability and post-launch iteration support. The team of 100–200 data scientists and ML engineers focuses exclusively on AI and data science, with no legacy software development distraction.
Codiant
Codiant is a software development company headquartered in Illinois, USA with a development centre in India and offices in the UK, Australia, and UAE, employing 240+ full-time professionals. The company is a subsidiary of Yash Technologies and delivers custom AI and ML solutions alongside web and mobile development for startups and enterprises across five continents. Codiant holds ISO 9001 and ISO/IEC 27001:2013 certifications and has completed 700+ projects for 200+ active clients. The ML practice covers data engineering, model development, and integration into web and mobile platforms.
Services and capabilities: InData Labs vs Codiant
| Capability | InData Labs | Codiant |
|---|---|---|
| Custom ML development | ✓ | ✓ |
| Computer vision | ✓ | ✗ |
| NLP & text analytics | ✓ | ✓ |
| MLOps & deployment | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| ML consulting & strategy | ✓ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Dedicated team model | ✗ | ✓ |
Tech stack comparison: InData Labs vs Codiant
| Framework / platform | InData Labs | Codiant |
|---|---|---|
| Python | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| Scikit-learn | ✓ | ✓ |
| AWS SageMaker | ✓ | N/A |
| MLflow | ✓ | N/A |
| Hugging Face | ✓ | N/A |
| LangChain | N/A | N/A |
| Docker/Kubernetes | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: InData Labs vs Codiant
| Criterion | InData Labs | Codiant |
|---|---|---|
| Minimum engagement | $25K | $15K |
| Engagement models | Fixed project, Time & materials, Retainer | Fixed project, Dedicated team, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: InData Labs vs Codiant
| Dimension | InData Labs | Codiant |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | FinTech, Healthcare, SaaS | Healthcare, Fintech, E-commerce |
| Best use cases | Custom predictive analytics for e-commerce personalisation and recommendation, Computer vision systems for healthcare diagnostics and imaging | ML features integrated into mobile and web application product builds, Predictive analytics for e-commerce product recommendation and personalisation |
| Typical project type | Fixed project | Fixed project |
InData Labs vs Codiant: pros and cons
| InData Labs | |
|---|---|
| + | Pure-play data science focus — no distraction from web or mobile side-practice work |
| + | 4.9/5 on Clutch with 18 independently verified client reviews |
| + | Covers the full ML lifecycle from data preparation through production deployment |
| + | Documented post-launch iteration process reduces post-deployment risk |
| + | Flexible pricing: fixed, T&M, and retainer engagement options available |
| - | Smaller team size limits simultaneous capacity for very large multi-model programmes |
| - | Primary delivery in EU time zones; US clients should confirm daily overlap hours |
| - | Minimum engagement may price out very early-stage PoC exploration |
| Codiant | |
|---|---|
| + | ISO 9001 and 27001 certifications for quality and security process assurance |
| + | Yash Technologies parent provides financial stability and enterprise credibility |
| + | 240+ professionals with multi-continent delivery capability across 5 geographies |
| + | $15K minimum engagement is accessible for startup and small company budgets |
| + | 700+ completed projects provides delivery track record across multiple industries |
| - | AI/ML is one of multiple service lines at a broadly-positioned development company |
| - | Yash Technologies acquisition means company culture may differ from independent AI-first firms |
| - | Smaller team limits capacity for very large or complex enterprise ML programmes |
Who should choose InData Labs?
InData Labs is the right choice for mid-market companies needing custom production-grade ML systems with verified delivery track record and ongoing support.
Pure-play data science boutique with 4.9/5 Clutch rating across 18 independent reviews and documented post-launch iteration model. Minimum engagement starts at $25K. Works best with clients in FinTech, Healthcare, SaaS, Retail, Logistics, E-commerce.
Who should choose Codiant?
Codiant is the right choice for startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost.
Yash Technologies subsidiary with ISO 9001 and 27001 certifications, multi-continent delivery, and 700+ completed projects for 200+ active clients. Minimum engagement starts at $15K. Works best with clients in Healthcare, Fintech, E-commerce, SaaS, Logistics.
Decision matrix: InData Labs vs Codiant
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | InData Labs |
| You need a large dedicated team for an ongoing programme | Codiant |
| Your budget is at the lower end | Codiant |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | InData Labs |
Use case fit: InData Labs vs Codiant
| Use case | InData Labs fit | Codiant fit | Winner |
|---|---|---|---|
| Custom predictive analytics for e-commerce personalisation and recommendation | Strong | Limited | InData Labs |
| Computer vision systems for healthcare diagnostics and imaging | Strong | Limited | InData Labs |
| ML features integrated into mobile and web application product builds | Limited | Strong | Codiant |
| Predictive analytics for e-commerce product recommendation and personalisation | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs Codiant
InData Labs (4.8/5) is the stronger overall choice for most Machine Learning Development projects. Pure-play data science boutique with 4.9/5 Clutch rating across 18 independent reviews and documented post-launch iteration model. It is best for mid-market companies needing custom production-grade ML systems with verified delivery track record and ongoing support.
Codiant (3.6/5) is the better choice when startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost. If your situation matches those criteria, Codiant is a competitive option.
Related comparisons
InData Labs vs Codiant FAQ
Is InData Labs better than Codiant?
InData Labs (4.8/5) scores higher overall, but "better" depends on your use case. InData Labs is better for mid-market companies needing custom production-grade ML systems with verified delivery track record and ongoing support. Codiant is better for startups and mid-market companies on five continents needing ML development integrated with web and mobile product builds at accessible cost.
How do InData Labs and Codiant differ in pricing?
InData Labs uses fixed project, t&m, retainer pricing with a minimum engagement of $25K. Codiant uses fixed project, dedicated team, t&m pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: InData Labs or Codiant?
Codiant 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 Codiant?
InData Labs's primary differentiator is: pure-play data science boutique with 4.9/5 clutch rating across 18 independent reviews and documented post-launch iteration model. Codiant's primary differentiator is: yash technologies subsidiary with iso 9001 and 27001 certifications, multi-continent delivery, and 700+ completed projects for 200+ active clients. They also differ in team size (100–200 vs 200–300), minimum engagement ($25K vs $15K), and primary industries served (FinTech, Healthcare vs Healthcare, Fintech).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.