InData Labs vs Modus Create: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.3/5) edges ahead of Modus Create (4.0/5) overall. InData Labs is the better choice for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks.. Modus Create is the stronger option for distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery.. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Modus Create: head-to-head summary
| Criterion | InData Labs | Modus Create |
|---|---|---|
| Founded | 2014 | 2011 |
| HQ | Nicosia, Cyprus (delivery center: Minsk, Belarus) | Reston, USA |
| Team size | 51–200 | 501–1,000 |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Best for | Companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks. | Distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery. |
| Pricing model | Project-based | Not published; project and dedicated team |
| Min. engagement | $25,000 | Not published |
| Primary tech stack | Python, Computer vision frameworks, NLP toolkits | Python, AWS, Data governance tooling |
| Industries served | Transportation/logistics, Retail, Finance | Technology/SaaS, Retail, Healthcare |
InData Labs vs Modus Create: overview
InData Labs
InData Labs is a data science consultancy founded in 2014 by Marat Karpeko, with a registered headquarters in Nicosia, Cyprus, and its primary research and development center in Minsk, Belarus. The company focuses on predictive analytics, natural language processing, and computer vision, delivering custom AI model development for clients ranging from logistics to retail. Published case studies include a freight-rate prediction model for a transportation company and a dog-face-identification model reporting 91.96 percent accuracy, giving it more quantified, checkable outcome data than many peers of similar size.
Modus Create
Modus Create is a fully remote, distributed product engineering company founded in 2011 and headquartered in Reston, Virginia, with team members spread across more than 55 countries. The company's AI/ML and data engineering practice includes AI Strategy Roadmap assessments and AI Data Foundation assessments intended to ensure underlying data is reliable and properly governed before or alongside model development work. Modus Create has partnered with technology providers including Atlassian, GitHub, and AWS, and has been recognized on the Inc. 5000 list for nine consecutive years.
Services and capabilities: InData Labs vs Modus Create
| Capability | InData Labs | Modus Create |
|---|---|---|
| Custom model training | ✓ | ✓ |
| Fine-tuning & adaptation | ✗ | ✗ |
| MLOps pipeline | ✗ | ✗ |
| Model deployment & serving | ✗ | ✗ |
| Data engineering for ML | ✓ | ✓ |
| ML infrastructure management | ✗ | ✗ |
| Computer vision | ✓ | ✗ |
| NLP & LLM development | ✓ | ✗ |
| Forecasting & time-series modeling | ✗ | ✗ |
| ML strategy consulting | ✗ | ✓ |
Tech stack comparison: InData Labs vs Modus Create
| Framework / platform | InData Labs | Modus Create |
|---|---|---|
| PyTorch | N/A | N/A |
| TensorFlow | N/A | N/A |
| MLflow | N/A | N/A |
| AWS SageMaker | N/A | N/A |
| Amazon Bedrock | N/A | N/A |
| Google Cloud | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Kubernetes | N/A | N/A |
| Snowflake | N/A | N/A |
| NVIDIA | N/A | N/A |
Pricing comparison: InData Labs vs Modus Create
| Criterion | InData Labs | Modus Create |
|---|---|---|
| Minimum engagement | $25,000 | Not published |
| Engagement models | Fixed project, Time & Material | Fixed project, Dedicated team, Assessment/audit engagement |
| Rate transparency | Minimum disclosed | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: InData Labs vs Modus Create
| Dimension | InData Labs | Modus Create |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Transportation/logistics, Retail, Finance | Technology/SaaS, Retail, Healthcare |
| Best use cases | Building a predictive pricing or demand-forecasting model for logistics or transportation, Developing a computer-vision classification model with a documented accuracy target | Running an AI Data Foundation assessment before committing to a full model-development engagement, Building an AI strategy roadmap for an organization new to machine learning adoption |
| Typical project type | Fixed project | Fixed project |
InData Labs vs Modus Create: pros and cons
| InData Labs | |
|---|---|
| + | Case studies include specific, quantified model accuracy figures rather than vague outcome claims. |
| + | Featured among Clutch's broader provider directory with a positive review sentiment on delivery timeliness. |
| + | Focused specialization in predictive analytics and computer vision avoids service-line dilution. |
| + | Recognized in a 2016 "Top 100 Big Data" listing, indicating an established track record. |
| - | Team size figures are inconsistent across sources (roughly 50–80 depending on source), so exact headcount is uncertain. |
| - | Registered HQ (Cyprus) differs from the primary delivery center (Belarus), which some buyers may want clarified given regional considerations. |
| - | Public tech-stack disclosure is limited beyond high-level specialization areas. |
| - | Fewer large, brand-name enterprise clients named publicly compared to bigger peers. |
| Modus Create | |
|---|---|
| + | Structured AI Data Foundation assessment reduces risk of building models on ungoverned or unreliable data. |
| + | Fully remote, globally distributed team (55+ countries) offers broad timezone coverage. |
| + | Nine consecutive years on the Inc. 5000 list signals sustained growth. |
| + | Technology partnerships with Atlassian, GitHub, and AWS support integrated delivery tooling. |
| - | AI/ML is one of several product engineering service lines rather than the company's sole specialization. |
| - | No clearly located aggregate Clutch/G2 star rating in available public sources. |
| - | Pricing model and minimum engagement are not published. |
| - | Fully remote delivery model may not suit buyers who prefer localized or on-site teams. |
Who should choose InData Labs?
InData Labs is the right choice for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks..
Publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims.. Minimum engagement starts at $25,000. Works best with clients in Transportation/logistics, Retail, Finance.
Who should choose Modus Create?
Modus Create is the right choice for distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery..
Structured AI Data Foundation assessment methodology that explicitly evaluates data readiness before committing to model development.. Minimum engagement starts at Not published. Works best with clients in Technology/SaaS, Retail, Healthcare.
Decision matrix: InData Labs vs Modus Create
| 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 | Modus Create |
| Your budget is at the lower end | Compare: InData Labs ($25,000) vs Modus Create (Not published) |
| 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 | Modus Create |
Use case fit: InData Labs vs Modus Create
| Use case | InData Labs fit | Modus Create fit | Winner |
|---|---|---|---|
| Building a predictive pricing or demand-forecasting model for logistics or transportation | Strong | Strong | Both equally |
| Developing a computer-vision classification model with a documented accuracy target | Strong | Limited | InData Labs |
| Running an AI Data Foundation assessment before committing to a full model-development engagement | Strong | Strong | Both equally |
| Building an AI strategy roadmap for an organization new to machine learning adoption | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| MLOps pipeline setup | Limited | Limited | Both equally |
Verdict: InData Labs vs Modus Create
InData Labs (4.3/5) is the stronger overall choice for most ML Model Development projects. Publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims.. It is best for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks..
Modus Create (4.0/5) is the better choice when distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery.. If your situation matches those criteria, Modus Create is a competitive option.
Related comparisons
InData Labs vs Modus Create FAQ
Is InData Labs better than Modus Create?
InData Labs (4.3/5) scores higher overall, but "better" depends on your use case. InData Labs is better for companies needing a focused predictive-analytics or computer-vision model with clearly documented accuracy benchmarks.. Modus Create is better for distributed organizations wanting a remote-first partner that pairs data-foundation assessments with AI/ML model delivery..
How do InData Labs and Modus Create differ in pricing?
InData Labs uses project-based pricing with a minimum engagement of $25,000. Modus Create uses not published; project and dedicated team pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: InData Labs or Modus Create?
Modus Create 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 Modus Create?
InData Labs's primary differentiator is: publishes concrete, quantified accuracy figures in its case studies rather than only qualitative outcome claims.. Modus Create's primary differentiator is: structured ai data foundation assessment methodology that explicitly evaluates data readiness before committing to model development.. They also differ in team size (51–200 vs 501–1,000), minimum engagement ($25,000 vs Not published), and primary industries served (Transportation/logistics, Retail vs Technology/SaaS, Retail).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.