Yalantis
Compliance-first engineering firm delivering ML consulting and solutions across IoT, healthcare, and enterprise.
What is Yalantis?
Yalantis was founded in 2008 and operates with a focus on compliance-first IoT and software engineering alongside machine learning consulting. The company's ML team provides domain-specific consulting, model deployment, and ongoing support, with depth in regulated industries including healthcare and fintech. ML consultants hold master's degrees in machine learning and have production data science experience. (Founded year per Tracxn; specialisation per Yalantis official website.)
Yalantis was founded in 2008 and is headquartered in Kyiv, Ukraine. The firm employs 200–400 people and works primarily with clients in healthcare, fintech, saas, logistics, manufacturing sectors. Its primary differentiator is: Compliance-first ML delivery — particularly strong for healthcare and regulated fintech with IoT integration needs.
Yalantis tech stack and services
| Service area |
|---|
| ML Consulting |
| Custom ML Build |
| Predictive Analytics |
| NLP / LLM |
| Computer Vision |
Yalantis use cases
Short answer: Yalantis is best suited for Healthcare, fintech — compliance-aware ML plus IoT.
| Use case |
|---|
| Compliance-aware ML model for healthcare data |
| Predictive analytics for fintech risk management |
| IoT sensor data ML pipeline |
| Computer vision for industrial monitoring |
| ML consulting and strategy for regulated enterprise |
Yalantis pricing
Short answer: Yalantis uses a fixed project, t&m pricing approach. Minimum engagement starts at $25K+.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $25K+ | Well-defined scope |
| T&M | Variable; depends on team size | Large programmes or team augmentation |
| Retainer | Monthly rate; not public | Ongoing AI engineering |
Yalantis pros and cons
| Advantages | Things to consider |
|---|---|
| +Compliance-first approach for regulated healthcare and fintech projects | -Ukraine-based delivery carries geographic risk considerations for some clients |
| +Full-lifecycle ML: from consulting through deployment and support | -Less suited to pure data science research or exploratory projects |
| +Master's-qualified ML consultants — verifiable technical depth | |
| +IoT integration experience alongside ML — rare combination |
Yalantis vs alternatives
How Yalantis 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 |
| InData Labs | Fintech, healthcare, SaaS — production ML with GenAI/RAG. | Deep ML and GenAI specialist with 10+ years of production deployments across regulated industries | 4.6 | 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 |
| 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 |
Yalantis FAQ
What is Yalantis?
Yalantis was founded in 2008 and operates with a focus on compliance-first IoT and software engineering alongside machine learning consulting. The company's ML team provides domain-specific consulting, model deployment, and ongoing support, with depth in regulated industries including healthcare and fintech. ML consultants hold master's degrees in machine learning and have production data science experience. (Founded year per Tracxn; specialisation per Yalantis official website.)
How much does Yalantis charge?
Yalantis uses fixed project, t&m pricing. Minimum engagement starts at $25K+. A discovery call is required to get project-specific quotes.
What tech stack does Yalantis use?
Yalantis works with Python, TensorFlow, PyTorch, scikit-learn, AWS, Azure, IoT platforms. Primary industries served include healthcare, fintech, saas, logistics, manufacturing.
Is Yalantis right for enterprise?
Healthcare, fintech — compliance-aware ML plus IoT. 200–400 team size. Key consideration: Ukraine-based delivery carries geographic risk considerations for some clients.
What are the best Yalantis alternatives?
The best alternatives to Yalantis depend on your use case. Top options are:
- Tensorway: full-lifecycle ml ownership — model design, training infrastructure, and drift monitoring in one team
- InData Labs: deep ml and genai specialist with 10+ years of production deployments across regulated industries
- Artefact: enterprise ml at 1,500-consultant scale across 26 countries — strategy, deployment, and ai factory in one firm