InData Labs
Editor's pick #1Production-grade AI and machine learning for fintech, healthcare, and SaaS since 2014.
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
| Service area |
|---|
| Custom ML Build |
| ML Consulting |
| NLP / LLM |
| Computer Vision |
| Predictive Analytics |
| Data Engineering |
InData Labs use cases
Short answer: InData Labs is best suited for Fintech, healthcare, SaaS — production ML with GenAI/RAG.
| Use case |
|---|
| GenAI and RAG-based knowledge management system |
| Churn prediction model for SaaS |
| Computer vision for medical imaging |
| Fraud detection for fintech |
| Recommendation system for e-commerce |
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 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 |
|---|---|---|---|---|
| Tensorway | Mid-market teams, full-lifecycle ML ownership. | Full-lifecycle ML ownership — model design, training infrastructure, and drift monitoring in one team | 4.8 | Full comparison |
| Artefact | Large enterprises, industrial-scale ML and data strategy. | Enterprise ML at 1,500-consultant scale across 26 countries — strategy, deployment, and AI factory in one firm | 4.5 | Full comparison |
| N-iX | Enterprise teams, ML plus cloud engineering, European delivery. | 2,400+ engineers covering ML, cloud, and data under one firm — strong for large multi-track programmes | 4.4 | Full comparison |
| Sigmoid | Fortune 500 retail/CPG/financial firms, AI-first data platforms. | Sequoia-backed AI and data engineering specialist with a Fortune 500 client portfolio in retail and CPG | 4.3 | Full comparison |
| Scopic | Healthcare, fintech enterprises — genuinely custom ML. | 20-year track record of custom ML engineering across 1,000+ projects — no API-wrapper shortcuts | 4.2 | Full comparison |
| Miquido | Product companies, ML embedded in mobile/web products. | AI-plus-product development — ML capabilities integrated with UX engineering, not delivered as a standalone model | 4.2 | Full comparison |
| NineTwoThree AI Studio | Mid-market scale-ups, boutique AI/ML studio. | Inc. 5000 AI studio with Clutch Top 50 ranking — boutique delivery model with direct principal access | 4.1 | Full comparison |
| RTS Labs | US finance/healthcare firms, pilot-to-production AI. | Pilot-to-production ML with deep data engineering roots — Snowflake, Azure, and AWS native | 4.1 | Full comparison |
| SciForce | Production NLP/CV systems, cost-effective Eastern Europe. | End-to-end ML delivery — from requirements to post-launch support — with NLP and computer vision depth | 4.0 | Full comparison |
| LeewayHertz | Enterprise clients, AI engineering, Hackett-backed. | Backed by The Hackett Group since Sept 2024 — AI engineering within an enterprise transformation consulting firm | 4.0 | Full comparison |
| DATAFOREST | US/EU companies, affordable AI, verified Clutch ratings. | 4.9-star Clutch rating across 27 verified reviews — one of the highest-rated AI firms in Eastern Europe | 4.0 | Full comparison |
| Kanerika | US enterprises, AI strategy plus data engineering. | Enterprise data-to-value specialist — ML consulting plus data integration and process automation in one engagement | 4.0 | Full comparison |
| DataArt | Enterprises, established firm, fintech/travel ML depth. | 1997-founded, 5,700-engineer global firm — enterprise scale and continuity across ML and software in fintech and travel | 3.9 | Full comparison |
| ELEKS | Enterprise clients, ML within full-service consulting. | 30+ years of enterprise software delivery — ML within a stable, large-org structure for risk-averse buyers | 3.9 | Full comparison |
| Yalantis | Healthcare, fintech — compliance-aware ML plus IoT. | Compliance-first ML delivery — particularly strong for healthcare and regulated fintech with IoT integration needs | 3.9 | Full comparison |
| Avenga | European enterprises, large-scale ML transformation. | Formed from a 2019 merger — 3,800+ engineers across Europe for large ML and digital transformation programmes | 3.9 | Full comparison |
| Intellectsoft | Fortune 500, AI modernisation of legacy systems. | AI modernisation specialist for Fortune 500 mission-critical systems — legacy transformation, not greenfield | 3.8 | Full comparison |
| Azumo | US companies, cost-effective Latin American nearshore ML. | Latin American nearshore delivery — US time-zone alignment with rates below fully on-shore alternatives | 3.8 | Full comparison |
| Iflexion | Enterprises, ML within software modernisation. | 25 years of software delivery with ML integrated — 800+ clients provide a verified delivery track record | 3.8 | Full comparison |
| Altamira | Companies, production-ready AI agents from day one. | AI-native product-build firm — delivers fully integrated, trained AI agents ready for production from day one | 3.8 | Full comparison |
| Maruti Techlabs | Mid-market companies, cost-effective US/India ML delivery. | Dual US-India delivery with AWS Marketplace listing — cost-effective ML for mid-market budgets | 3.8 | Full comparison |
| Keyrus | International enterprises, industrial-AI implementation. | From experimental AI to industrial AI — consulting group specialising in productionising ML for large organisations | 3.8 | Full comparison |
| Itransition | Global enterprises, ML within full software delivery. | 25+ years of full-cycle delivery to 30+ countries — ML within a large proven software engineering organisation | 3.8 | Full comparison |
| Turing | Companies needing rapid, vetted ML staff augmentation. | AI-vetted 4M+ developer network — fastest route to pre-screened ML talent for staff augmentation | 3.8 | Full comparison |
| Acropolium | SaaS startups, ML features in custom product builds. | 22 years of bespoke product engineering — ML as a product feature, not a standalone model delivery | 3.8 | Full comparison |
| Kanda Software | Healthcare, pharma — compliance-aware AI development. | Regulatory-domain ML specialist — AI for pharma and healthcare with compliance and IP ownership built in | 3.7 | Full comparison |
| Binariks | Companies, cost-effective ML with cloud/IoT integration. | Multi-cloud and IoT-integrated ML delivery — AWS, GCP, and Azure with IoT sensor data pipelines | 3.7 | Full comparison |
| Centric Consulting | US enterprises, ML within business transformation. | Business-outcome ML consulting — AI within management transformation, not pure technology delivery | 3.7 | Full comparison |
| Space-O Technologies | Startups/SMBs, accessible ML in healthcare/e-commerce. | Budget-accessible ML for startups — low minimum engagement with India-based rate advantage | 3.7 | Full comparison |
| Modak | Large enterprises, AI-driven data modernisation. | ML-powered data engineering — uses ML itself to accelerate data prep and modernisation at enterprise scale | 3.7 | Full comparison |
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, SaaS — production ML with GenAI/RAG. 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