InData Labs vs Deviniti: full comparison for 2026
Last updated: July 2026
Quick verdict
InData Labs (4.4/5) edges ahead of Deviniti (4.0/5) overall. InData Labs is the better choice for companies wanting a decade-plus data science track record with in-house R&D rather than a pure project-delivery shop.. Deviniti is the stronger option for enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots.. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs Deviniti: head-to-head summary
| Criterion | InData Labs | Deviniti |
|---|---|---|
| Founded | 2014 | 2004 |
| HQ | Nicosia, Cyprus (R&D and delivery centers in Lithuania and the US) | Wrocław, Poland |
| Team size | 80+ | 300+ |
| Rating | 4.4 / 5 | 4.0 / 5 |
| Best for | Companies wanting a decade-plus data science track record with in-house R&D rather than a pure project-delivery shop. | Enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots. |
| Pricing model | Fixed project, Time & Materials | Fixed project, staff augmentation |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, Generative AI/GPT tooling, Computer vision frameworks | Python, LLM fine-tuning tooling, RAG architectures |
| Industries served | Cross-industry, Predictive Analytics | Financial Institutions, Regulated enterprise IT |
InData Labs vs Deviniti: overview
InData Labs
InData Labs is a data science and AI consultancy legally headquartered in Nicosia, Cyprus, founded in 2014 by video-gaming industry veteran Marat Karpeko, with R&D and delivery centers in Lithuania and the US. The 80+ person firm runs its own R&D center and covers a wide technical band from generative AI and GPT integration through predictive analytics, forecasting, and computer vision. Its Cyprus legal HQ gives clients an EU-entity contracting structure alongside nearshore delivery capacity.
Deviniti
Deviniti is a Wrocław, Poland software house founded in 2004, with 300+ specialists serving over 15,000 clients across 38 countries (per company website). It holds 50+ Atlassian-certified professionals and was a 2024–2025 Atlassian Partner of the Year finalist for Emerging Markets, and has more recently built out generative AI, custom AI agent, self-hosted LLM, LLM fine-tuning, and RAG architecture capabilities, including contributions to the open-source Bielik.AI project.
Services and capabilities: InData Labs vs Deviniti
| Capability | InData Labs | Deviniti |
|---|---|---|
| ML Development | ✓ | ✓ |
| AI Consulting | ✓ | ✓ |
| Computer Vision | ✗ | ✗ |
| NLP | ✗ | ✗ |
| Generative AI | ✓ | ✓ |
| MLOps | ✗ | ✗ |
| Data Engineering | ✓ | ✗ |
| Staff Augmentation | ✗ | ✓ |
Tech stack comparison: InData Labs vs Deviniti
| Framework / platform | InData Labs | Deviniti |
|---|---|---|
| Python | ✓ | ✓ |
| AWS | N/A | N/A |
| Microsoft Azure | N/A | N/A |
| Google Cloud | N/A | N/A |
| Kubernetes | N/A | N/A |
| PyTorch | N/A | N/A |
| LangChain | N/A | N/A |
| Databricks | N/A | N/A |
Pricing comparison: InData Labs vs Deviniti
| Criterion | InData Labs | Deviniti |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Fixed project, Time & Materials | Fixed project, Staff augmentation, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Enterprise / mid-market | Enterprise / mid-market |
Target audience comparison: InData Labs vs Deviniti
| Dimension | InData Labs | Deviniti |
|---|---|---|
| Best company size | Startup to mid-market | Mid-market to enterprise |
| Best industries | Cross-industry, Predictive Analytics | Financial Institutions, Regulated enterprise IT |
| Best use cases | Generative AI and GPT integration projects, Predictive analytics and forecasting | Self-hosted LLM and RAG system development, AI chatbot and knowledge-base solutions for enterprises |
| Typical project type | Fixed project | Fixed project |
InData Labs vs Deviniti: pros and cons
| InData Labs | |
|---|---|
| + | Founded 2014 — one of the longer-running boutique data science firms in this list |
| + | In-house R&D center is a differentiator versus pure staff-augmentation vendors |
| + | Cyprus legal HQ with Lithuania/US delivery centers gives EU-entity contracting plus nearshore delivery |
| + | Broad technical range from generative AI to classic forecasting and computer vision |
| - | 80+ employee band is imprecise — exact current headcount is not independently published |
| - | Legal HQ (Cyprus) is a smaller AI hub than its Lithuania delivery center, which may matter to buyers wanting an on-the-ground presence |
| - | Pricing model and minimum engagement are not published |
| Deviniti | |
|---|---|
| + | 300+ specialists and 15,000+ clients across 38 countries show significant delivery scale (per company website) |
| + | Contributions to the open-source Bielik.AI project demonstrate genuine LLM/NLP engineering, not just integration work |
| + | Deep Atlassian-ecosystem expertise is a strong complementary asset for enterprise clients running Jira/Confluence-based workflows |
| + | Founded 2004 — two decades of enterprise software delivery experience |
| - | Generative AI and RAG practice is newer than its core Atlassian and enterprise-software business, so ML-specific track record is shorter than the overall company history suggests |
| - | 300+ specialists are split across Atlassian consulting and AI/software delivery, so dedicated AI headcount is unclear |
| - | 15,000+ client claim is per company marketing and not independently broken down by service line |
Who should choose InData Labs?
InData Labs is the right choice for companies wanting a decade-plus data science track record with in-house R&D rather than a pure project-delivery shop..
Runs its own R&D center rather than purely project-based delivery, spanning generative AI/GPT integration through classic predictive analytics and computer vision.. Minimum engagement starts at Not published. Works best with clients in Cross-industry, Predictive Analytics.
Who should choose Deviniti?
Deviniti is the right choice for enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots..
50+ Atlassian-certified professionals and Atlassian Partner of the Year finalist status give it unusually strong enterprise-IT integration credibility alongside its generative AI practice and Bielik.AI open-source contributions.. Minimum engagement starts at Not published. Works best with clients in Financial Institutions, Regulated enterprise IT.
Decision matrix: InData Labs vs Deviniti
| 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 | Deviniti |
| Your budget is at the lower end | Compare: InData Labs (Not published) vs Deviniti (Not published) |
| You need specialist depth in a specific vertical | InData Labs |
| You need staff augmentation or team extension | Deviniti |
| You need consulting before committing to a build | InData Labs |
Use case fit: InData Labs vs Deviniti
| Use case | InData Labs fit | Deviniti fit | Winner |
|---|---|---|---|
| Generative AI and GPT integration projects | Strong | Strong | Both equally |
| Predictive analytics and forecasting | Strong | Limited | InData Labs |
| Self-hosted LLM and RAG system development | Limited | Strong | Deviniti |
| AI chatbot and knowledge-base solutions for enterprises | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs Deviniti
InData Labs (4.4/5) is the stronger overall choice for most Machine Learning Development projects. Runs its own R&D center rather than purely project-based delivery, spanning generative AI/GPT integration through classic predictive analytics and computer vision.. It is best for companies wanting a decade-plus data science track record with in-house R&D rather than a pure project-delivery shop..
Deviniti (4.0/5) is the better choice when enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots.. If your situation matches those criteria, Deviniti is a competitive option.
Related comparisons
InData Labs vs Deviniti FAQ
Is InData Labs better than Deviniti?
InData Labs (4.4/5) scores higher overall, but "better" depends on your use case. InData Labs is better for companies wanting a decade-plus data science track record with in-house R&D rather than a pure project-delivery shop.. Deviniti is better for enterprises in regulated or complex sectors wanting generative AI, RAG, and LLM work delivered by a vendor with deep enterprise-software (Atlassian ecosystem) roots..
How do InData Labs and Deviniti differ in pricing?
InData Labs uses fixed project, time & materials pricing with a minimum engagement of Not published. Deviniti uses fixed project, staff augmentation 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 Deviniti?
Deviniti 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 Deviniti?
InData Labs's primary differentiator is: runs its own r&d center rather than purely project-based delivery, spanning generative ai/gpt integration through classic predictive analytics and computer vision.. Deviniti's primary differentiator is: 50+ atlassian-certified professionals and atlassian partner of the year finalist status give it unusually strong enterprise-it integration credibility alongside its generative ai practice and bielik.ai open-source contributions.. They also differ in team size (80+ vs 300+), minimum engagement (Not published vs Not published), and primary industries served (Cross-industry, Predictive Analytics vs Financial Institutions, Regulated enterprise IT).
Last reviewed: July 2026. Verify all details directly with each company before making a decision.