InData Labs vs ELEKS: full comparison for 2026
Quick verdict
InData Labs (4.6/5) edges ahead of ELEKS (3.9/5) overall. InData Labs is the better choice for Fintech, healthcare, SaaS — production ML with GenAI/RAG. ELEKS is the stronger option for enterprise clients, ML within full-service consulting. The right choice depends on your project size, budget, and required tech stack.
InData Labs vs ELEKS: head-to-head summary
| Criterion | InData Labs | ELEKS |
|---|---|---|
| Founded | 2014 | 1991 |
| HQ | Nicosia, Cyprus | Lviv, Ukraine |
| Team size | 80+ | 2,000+ |
| Rating | 4.6 / 5 | 3.9 / 5 |
| Primary differentiator | Deep ML and GenAI specialist with 10+ years of production deployments across regulated industries | 30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers |
| Pricing model | Fixed project, T&M | T&M, dedicated team |
| Min. engagement | $15K | $50K+ |
| Primary tech stack | Python, TensorFlow, PyTorch | Python, TensorFlow, PyTorch |
| Industries served | fintech, healthcare, saas, retail, logistics | financial, healthcare, manufacturing, retail, logistics |
InData Labs vs ELEKS: overview
InData Labs
InData Labs is a data science and AI consultancy founded in 2014, with headquarters in Nicosia, Cyprus and offices in Lithuania and the US. The firm covers the full ML stack: generative AI (LLMs, RAG systems, AI agents), predictive ML (recommendation engines, churn models, computer vision), data engineering, and DevOps for AI infrastructure. With 80+ data science professionals, it focuses on mid-market clients in fintech, healthcare, SaaS, retail, and logistics. (Team size per company LinkedIn; independently verified.)
ELEKS
ELEKS was established in 1991 and is headquartered in Lviv, Ukraine, with offices across Europe and North America. The company has 2,000+ engineers and delivers technology consulting, AI/ML services, and enterprise software for Fortune 500 clients globally. ML services include predictive analytics, computer vision, NLP, and intelligent automation. ELEKS celebrated its 30th anniversary in 2021. (Founding year and team size per ELEKS official website and KyivPost article.)
Services and capabilities: InData Labs vs ELEKS
| Capability | InData Labs | ELEKS |
|---|---|---|
| Custom ML build | ✓ | ✓ |
| ML consulting | ✓ | ✓ |
| Computer vision | ✓ | ✓ |
| NLP / LLM | ✓ | ✓ |
| Predictive analytics | ✓ | ✗ |
| MLOps | ✗ | ✗ |
| Data engineering | ✓ | ✓ |
| Generative AI | ✗ | ✗ |
| Staff augmentation | ✗ | ✗ |
| Fixed-price projects | ✓ | ✗ |
| Dedicated team model | ✗ | ✓ |
Tech stack comparison: InData Labs vs ELEKS
| Framework / platform | InData Labs | ELEKS |
|---|---|---|
| Python | ✓ | ✓ |
| TensorFlow | ✓ | ✓ |
| PyTorch | ✓ | ✓ |
| AWS SageMaker | N/A | N/A |
| Azure ML | N/A | N/A |
Pricing comparison: InData Labs vs ELEKS
| Criterion | InData Labs | ELEKS |
|---|---|---|
| Minimum engagement | $15K | $50K+ |
| Engagement models | Fixed project, T&M | T&M, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: InData Labs vs ELEKS
| Dimension | InData Labs | ELEKS |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | fintech, healthcare, saas | financial, healthcare, manufacturing |
| Best use cases | GenAI and RAG-based knowledge management system, Churn prediction model for SaaS | ML integration into enterprise ERP or CRM, Computer vision for manufacturing quality control |
| Typical project type | Fixed project | T&M |
InData Labs vs ELEKS: pros and cons
| InData Labs | |
|---|---|
| + | 10+ years of pure ML/AI focus — not a repositioned generalist practice |
| + | Production-grade GenAI including RAG and AI agent systems |
| + | Covers the full stack: ML engineering, data engineering, and MLOps |
| + | Strong track record in regulated industries (fintech, healthcare) |
| + | Verified Clutch and DesignRush ratings across multiple client reviews |
| - | Smaller team (80+) limits capacity for very large concurrent programmes |
| - | Not a staffing platform — less suited to pure team augmentation needs |
| ELEKS | |
|---|---|
| + | 30+ years of enterprise delivery history — very low company risk |
| + | 2,000+ engineers across multiple disciplines |
| + | Proven Fortune 500 delivery capability across multiple verticals |
| + | Wide industry coverage including manufacturing and financial services |
| - | ML practice is secondary to broader software engineering — not ML-first |
| - | Ukraine-based delivery carries geographic risk considerations for some clients |
| - | Less agile than boutique ML specialists for short exploratory projects |
Who should choose InData Labs?
A typical fit: GenAI and RAG-based knowledge management system.
Deep ML and GenAI specialist with 10+ years of production deployments across regulated industries. Minimum engagement starts at $15K. Works best with clients in fintech, healthcare, saas, retail, logistics.
Who should choose ELEKS?
A typical fit: ML integration into enterprise ERP or CRM.
30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers. Minimum engagement starts at $50K+. Works best with clients in financial, healthcare, manufacturing, retail, logistics.
Decision matrix: InData Labs vs ELEKS
| 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 | ELEKS |
| Your budget is at the lower end | InData Labs |
| 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 ELEKS
| Use case | InData Labs fit | ELEKS fit | Winner |
|---|---|---|---|
| GenAI and RAG-based knowledge management system | Strong | Limited | InData Labs |
| Churn prediction model for SaaS | Strong | Limited | InData Labs |
| ML integration into enterprise ERP or CRM | Limited | Strong | ELEKS |
| Computer vision for manufacturing quality control | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: InData Labs vs ELEKS
InData Labs (4.6/5) is the stronger overall choice for most Machine Learning projects. Deep ML and GenAI specialist with 10+ years of production deployments across regulated industries.
ELEKS (3.9/5) is worth a look if you need computer vision for manufacturing quality control. If your situation matches that, ELEKS is a competitive option.
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InData Labs vs ELEKS FAQ
Is InData Labs better than ELEKS?
InData Labs (4.6/5) scores higher overall, but "better" depends on your use case. InData Labs's strongest advantage: 10+ years of pure ML/AI focus — not a repositioned generalist practice. ELEKS's strongest advantage: 30+ years of enterprise delivery history — very low company risk.
How do InData Labs and ELEKS differ in pricing?
InData Labs uses fixed project, t&m pricing with a minimum engagement of $15K. ELEKS uses t&m, dedicated team pricing with a minimum engagement of $50K+. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: InData Labs or ELEKS?
ELEKS is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each agency before shortlisting.
What are the main differences between InData Labs and ELEKS?
InData Labs's primary differentiator is: deep ML and GenAI specialist with 10+ years of production deployments across regulated industries. ELEKS's primary differentiator is: 30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers. They also differ in team size (80+ vs 2,000+), minimum engagement ($15K vs $50K+), and primary industries served (fintech, healthcare vs financial, healthcare).