Best Machine Learning Agencies

InData Labs

Editor's pick #1

Production-grade AI and machine learning for fintech, healthcare, and SaaS since 2014.

Founded 2014 | Nicosia, Cyprus | 80+ employees | Last updated: July 2026
custom-ml-buildml-consultingnlpcomputer-visionpredictive-analyticsdata-engineering

What is 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.)

InData Labs was founded in 2014 and is headquartered in Nicosia, Cyprus. The firm employs 80+ people and works primarily with clients in fintech, healthcare, saas, retail, logistics sectors. Its primary differentiator is: Deep ML and GenAI specialist with 10+ years of production deployments across regulated industries.

InData Labs tech stack and services

PythonTensorFlowPyTorchscikit-learnLLMsRAGAWSGoogle CloudApache Spark
Service area Details
GenAI and RAG-based knowledge management system Available for fintech, healthcare, saas, retail, logistics clients
Churn prediction model for SaaS Available for fintech, healthcare, saas, retail, logistics clients
Computer vision for medical imaging Available for fintech, healthcare, saas, retail, logistics clients
Fraud detection for fintech Available for fintech, healthcare, saas, retail, logistics clients
Recommendation system for e-commerce Available for fintech, healthcare, saas, retail, logistics clients

InData Labs use cases

Short answer: InData Labs is best suited for fintech, healthcare, and SaaS companies needing production-grade ML including GenAI and RAG systems.

Use case Industries Approach
GenAI and RAG-based knowledge management system fintech, healthcare Python, TensorFlow
Churn prediction model for SaaS fintech, healthcare Python, TensorFlow
Computer vision for medical imaging fintech, healthcare Python, TensorFlow
Fraud detection for fintech fintech, healthcare Python, TensorFlow
Recommendation system for e-commerce fintech, healthcare Python, TensorFlow

InData Labs pricing

Short answer: InData Labs uses a fixed project, t&m pricing approach. Minimum engagement starts at $15K.

Engagement model Typical range Best for
Fixed project From $15K Well-defined scope
T&M Variable; depends on team size Large programmes or team augmentation
InData Labs does not publish a public rate card. Contact them directly via their website to get project-specific pricing.

InData Labs pros and cons

Advantages Things to consider
+10+ years of pure ML/AI focus — not a repositioned generalist practice -Smaller team (80+) limits capacity for very large concurrent programmes
+Production-grade GenAI including RAG and AI agent systems -Not a staffing platform — less suited to pure team augmentation needs
+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

InData Labs vs alternatives

How InData Labs compares to the other top Machine Learning agencies.

Company Best for Key difference Rating Compare
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SciForce Companies building production NLP or computer vision systems... End-to-end ML delivery — from requirements to post-launch support — with NLP and computer vision depth 4.0 Full comparison
LeewayHertz Enterprise clients seeking AI product engineering backed by... Backed by The Hackett Group since Sept 2024 — AI engineering within an enterprise transformation consulting firm 4.0 Full comparison
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Yalantis Healthcare and fintech companies needing compliance-aware ML consulting... Compliance-first ML delivery — particularly strong for healthcare and regulated fintech with IoT integration needs 3.9 Full comparison
Avenga European enterprise clients seeking large-scale ML and digital... Formed from a 2019 merger — 3,800+ engineers across Europe for large ML and digital transformation programmes 3.9 Full comparison
Intellectsoft Fortune 500 enterprises needing AI modernisation of legacy... AI modernisation specialist for Fortune 500 mission-critical systems — legacy transformation, not greenfield 3.8 Full comparison
Azumo US companies seeking cost-effective nearshore ML development with... Latin American nearshore delivery — US time-zone alignment with rates below fully on-shore alternatives 3.8 Full comparison
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Turing Companies needing rapid access to vetted ML engineers... AI-vetted 4M+ developer network — fastest route to pre-screened ML talent for staff augmentation 3.8 Full comparison
Acropolium SaaS companies and mid-market startups needing ML features... 22 years of bespoke product engineering — ML as a product feature, not a standalone model delivery 3.8 Full comparison
Kanda Software Healthcare, pharma, and life sciences companies needing compliance-aware... Regulatory-domain ML specialist — AI for pharma and healthcare with compliance and IP ownership built in 3.7 Full comparison
Binariks Companies seeking cost-effective AI and ML engineering with... Multi-cloud and IoT-integrated ML delivery — AWS, GCP, and Azure with IoT sensor data pipelines 3.7 Full comparison
Centric Consulting US mid-to-large enterprises needing ML consulting integrated within... Business-outcome ML consulting — AI within management transformation, not pure technology delivery 3.7 Full comparison
Space-O Technologies Startups and SMBs seeking accessible, cost-effective ML development... Budget-accessible ML for startups — low minimum engagement with India-based rate advantage 3.7 Full comparison
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InData Labs FAQ

What is 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.)

How much does InData Labs charge?

InData Labs uses fixed project, t&m pricing. Minimum engagement starts at $15K. A discovery call is required to get project-specific quotes.

What tech stack does InData Labs use?

InData Labs works with Python, TensorFlow, PyTorch, scikit-learn, LLMs, RAG, AWS, Google Cloud, Apache Spark. Primary industries served include fintech, healthcare, saas, retail, logistics.

Is InData Labs right for enterprise?

Fintech, healthcare, and SaaS companies needing production-grade ML including GenAI and RAG systems. 80+ team size. Key consideration: Smaller team (80+) limits capacity for very large concurrent programmes.

What are the best InData Labs alternatives?

The best alternatives to InData Labs depend on your use case. Top options are:

  • Tensorway: full-lifecycle ml ownership — model design, training infrastructure, and drift monitoring in one team
  • Artefact: enterprise ml at 1,500-consultant scale across 26 countries — strategy, deployment, and ai factory in one firm
  • N-iX: 2,400+ engineers covering ml, cloud, and data under one firm — strong for large multi-track programmes
See full alternatives list

Compare InData Labs with other Machine Learning agencies

Last reviewed: July 2026. Verify all details directly with InData Labs before making a decision.