Best Machine Learning Development Services Companies

InData Labs vs Ciklum: full comparison for 2026

Last updated: July 2026

Quick verdict

InData Labs (4.8/5) edges ahead of Ciklum (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. Ciklum is the stronger option for global enterprises seeking AI features embedded in large-scale digital product programmes with Experience Engineering focus. The right choice depends on your project size, budget, and required tech stack.

InData Labs vs Ciklum: head-to-head summary

Criterion InData Labs Ciklum
Founded 2014 2002
HQ Nicosia, Cyprus London, UK
Team size 100–200 4,000+
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 Global enterprises seeking AI features embedded in large-scale digital product programmes with Experience Engineering focus
Pricing model Fixed project, T&M, retainer Dedicated team, T&M
Min. engagement $25K $100K
Primary tech stack Python, TensorFlow, PyTorch Python, LangChain, OpenAI API
Industries served FinTech, Healthcare, SaaS, Retail, Logistics, E-commerce Fintech, Healthcare, E-commerce, SaaS, Logistics

InData Labs vs Ciklum: 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.

Ciklum

Ciklum is a global Experience Engineering firm headquartered in London, UK, founded in 2002, with 4,000+ employees serving 250+ global enterprise clients. The company acquired GoSolve Group in 2025, adding cloud-native development and high-performance computing capability. Ciklum's AI services include generative AI development, ML integration into digital products, and AI-powered SDLC acceleration. The firm delivers next-generation product engineering and AI-powered customer experiences for large enterprises and digital disruptors.

Services and capabilities: InData Labs vs Ciklum

Capability InData Labs Ciklum
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 Ciklum

Framework / platform InData Labs Ciklum
Python
PyTorch N/A
TensorFlow N/A
Scikit-learn N/A
AWS SageMaker N/A
MLflow
Hugging Face N/A
LangChain N/A
Docker/Kubernetes N/A N/A
Databricks N/A

Pricing comparison: InData Labs vs Ciklum

Criterion InData Labs Ciklum
Minimum engagement $25K $100K
Engagement models Fixed project, Time & materials, Retainer Dedicated team, Time & materials, Consulting retainer
Rate transparency Minimum disclosed Minimum disclosed
Price tier Accessible Accessible

Target audience comparison: InData Labs vs Ciklum

Dimension InData Labs Ciklum
Best company size Startup to mid-market Startup to mid-market
Best industries FinTech, Healthcare, SaaS Fintech, Healthcare, E-commerce
Best use cases Custom predictive analytics for e-commerce personalisation and recommendation, Computer vision systems for healthcare diagnostics and imaging Generative AI features integrated into large enterprise digital products, ML-powered personalisation for consumer-facing applications at scale
Typical project type Fixed project Dedicated team

InData Labs vs Ciklum: 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
Ciklum
+ 4,000+ employees serving 250+ enterprises demonstrates delivery scale and breadth
+ Generative AI services alongside traditional ML within product engineering
+ GoSolve acquisition (2025) adds cloud-native and high-performance computing depth
+ London HQ provides EU and UK enterprise relationship management
+ Experience Engineering focus connects ML outcomes to user-facing product features
- $100K minimum engagement limits access for smaller and mid-market companies
- AI is part of a broader service offering — not an ML-first or AI-specialist firm
- Less publicly documented in pure ML model research than boutique ML competitors

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 Ciklum?

Ciklum is the right choice for global enterprises seeking AI features embedded in large-scale digital product programmes with Experience Engineering focus.

4,000-person Experience Engineering firm with 250+ enterprise clients and generative AI delivery integrated into large product programmes. Minimum engagement starts at $100K. Works best with clients in Fintech, Healthcare, E-commerce, SaaS, Logistics.

Decision matrix: InData Labs vs Ciklum

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 Ciklum
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 Ciklum

Use case InData Labs fit Ciklum 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
Generative AI features integrated into large enterprise digital products Limited Strong Ciklum
ML-powered personalisation for consumer-facing applications at scale Limited Strong Ciklum
Fixed-price build Limited Limited Both equally
Staff augmentation Limited Limited Both equally

Verdict: InData Labs vs Ciklum

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.

Ciklum (3.6/5) is the better choice when global enterprises seeking AI features embedded in large-scale digital product programmes with Experience Engineering focus. If your situation matches those criteria, Ciklum is a competitive option.

Related comparisons

InData Labs vs Ciklum FAQ

Is InData Labs better than Ciklum?

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. Ciklum is better for global enterprises seeking AI features embedded in large-scale digital product programmes with Experience Engineering focus.

How do InData Labs and Ciklum differ in pricing?

InData Labs uses fixed project, t&m, retainer pricing with a minimum engagement of $25K. Ciklum uses dedicated team, t&m pricing with a minimum engagement of $100K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.

Which is better for enterprise: InData Labs or Ciklum?

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 company before shortlisting.

What are the main differences between InData Labs and Ciklum?

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. Ciklum's primary differentiator is: 4,000-person experience engineering firm with 250+ enterprise clients and generative ai delivery integrated into large product programmes. They also differ in team size (100–200 vs 4,000+), minimum engagement ($25K vs $100K), and primary industries served (FinTech, Healthcare vs Fintech, Healthcare).

Last reviewed: July 2026. Verify all details directly with each company before making a decision.