Oxagile
AI and ML development specialists with strong media, healthcare, and connected-care track records
Founded 2005 | Minsk, Belarus | 250–999 employees
custom-mlcomputer-visionnlpdata-engineeringmlops
What is Oxagile?
Oxagile is a software and AI development company founded in 2005 and headquartered in Minsk, Belarus, with 250–999 employees. The firm offers AI software development services with a focus on data-driven solutions for digital transformation. Oxagile is recognised for connected care AI in healthcare, computer vision in media and retail, and custom ML systems for enterprise clients across multiple verticals.
Oxagile was founded in 2005 and is headquartered in Minsk, Belarus. The firm employs 250–999 people and works primarily with clients in Healthcare & Life Sciences, Media & Entertainment, Financial Services, Manufacturing & Industrial, Retail & E-commerce sectors. Its primary differentiator is: Strong connected-care and healthcare AI track record combined with 40–60% cost advantage versus US equivalents.
Oxagile tech stack and services
PythonTensorFlowOpenCVKerasAWSGCPScikit-learnONNX
| Service area |
|---|
| Custom ML Development |
| Computer Vision |
| NLP & LLMs |
| Data Engineering |
| MLOps & Deployment |
Oxagile use cases
Short answer: Oxagile is best suited for Healthcare/media/retail enterprises, cost-effective Eastern European ML.
| Use case |
|---|
| Connected care AI for remote patient monitoring and telemedicine platform |
| Computer vision content moderation system for media streaming service |
| Healthcare imaging AI for radiology anomaly detection with PACS integration |
| Custom ML model for retail product recommendation and personalisation |
| Industrial computer vision inspection system for manufacturing quality control |
Oxagile pricing
Short answer: Oxagile uses a fixed project, t&m, dedicated team pricing approach. Minimum engagement starts at $20K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $20K | Well-defined scope |
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
Oxagile does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Oxagile pros and cons
| Advantages | Things to consider |
|---|---|
| +Competitive rates — 40–60% lower than US equivalents at comparable engineering quality | -Belarus-based delivery carries geopolitical risk and potential regulatory complications for some enterprises |
| +Connected care and healthcare imaging AI track record with PACS integration experience | -Less generative AI and LLM depth than firms with more recent AI-native practices |
| +Lower $20K minimum makes specialist ML accessible for budget-conscious projects | -Brand visibility lower than US-headquartered peers in North American procurement processes |
| +Computer vision depth in both media and industrial inspection use cases | |
| +Flexible three-model engagement covers fixed scope through long-term dedicated teams |
Oxagile vs alternatives
How Oxagile compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Mid-market teams, specialist CV/time-series/LLM delivery. | Boutique ML depth, with access to the 25-year enterprise delivery experience of its parent company — a rare combination in the ML services market | 4.9 | Full comparison |
| LeewayHertz | Businesses, GenAI/LLM integration plus custom ML. | Among the earliest boutique firms to build a structured GenAI delivery framework — deep LLM orchestration and RAG pipeline experience | 4.1 | Full comparison |
| Scopic | Companies needing genuinely custom ML architectures. | Engineers custom ML architectures from the ground up — not fine-tuned wrappers — with 20 years of production delivery discipline | 4.6 | Full comparison |
| InData Labs | Complex ML problems, deep data-science expertise. | Boutique firm with a track record of solving atypical, high-complexity ML problems that generalist shops decline or under-deliver on | 4.6 | Full comparison |
| DATAFOREST | Mid-market companies, full ML pipeline ownership. | Structured MLaaS delivery model — one team owns data engineering, model development, and post-deployment monitoring end-to-end | 4.5 | Full comparison |
| Forte Group | Regulated finance/insurance firms, audit-ready ML governance. | ML delivery built for regulated environments — model risk governance, audit trails, and compliance-aligned architecture are built in, not bolted on | 4.5 | Full comparison |
| RTS Labs | High-growth US companies, production-accountable ML partner. | Small by choice, senior by design — every project is staffed with senior practitioners accountable for post-launch performance, not just the plan | 4.5 | Full comparison |
| Quantiphi | Enterprises, cloud-native ML, top-tier AWS/GCP credentials. | AWS Premier and four-time Google Cloud Partner of the Year — the highest independently verified cloud ML credentials in the market | 4.4 | Full comparison |
| N-iX | EU/US enterprises, large dedicated teams, competitive rates. | Scale and depth in one package — 2,000+ engineers with a mature ML practice and competitive EU delivery rates | 4.4 | Full comparison |
| Miquido | Product companies, ML/GenAI embedded, fast time-to-demo. | GenAI and mobile ML integration in one team — a rare combination for companies building AI-native products for end users | 4.4 | Full comparison |
| Algoscale | Fortune 500 and growth-stage companies, cloud data lakehouse... | 100+ production ML deployments on AWS, Azure, and Snowflake — proven at enterprise scale with multiple cloud stacks | 4.3 | Full comparison |
| STX Next | Python-stack product companies, tightly integrated ML plus MLOps. | Europe's largest Python shop — ML is embedded in full-stack Python systems with MLOps, not delivered as an isolated model | 4.3 | Full comparison |
| Intellias | Enterprises, AWS-native ML, validated CV/NLP/RAG results. | AWS AI Services Competency with verified production benchmarks — 10x TCO reduction in aerial imagery and sub-8-second NLP query latency | 4.3 | Full comparison |
| ScienceSoft | Healthcare/finance orgs, HIPAA/PCI-DSS/SOC2-compliant ML. | Over 35 years of regulated IT delivery — compliance-aligned ML architecture is a core competency, not an add-on | 4.2 | Full comparison |
| Simform | Manufacturing/logistics enterprises, cloud-native ML plus IoT. | AWS Premier Partner specialising in connecting physical IoT sensor data to cloud-based ML models for predictive maintenance | 4.2 | Full comparison |
| Softeq | Companies building AI for edge and embedded hardware. | Hardware-to-cloud ML engineering — a rare full-stack capability covering embedded device AI through cloud model serving | 4.1 | Full comparison |
| Aimprosoft | SMBs, AI consulting and custom ML at accessible... | Full-cycle AI delivery from consulting through implementation, optimised for SMB budgets and timelines | 4.1 | Full comparison |
| Uvik Software | Teams with an existing ML codebase, embedded senior... | Senior-only ML engineer staffing — embedded in your stack, working in your tools, without agency overhead | 4.1 | Full comparison |
| Ciklum | FinTech, Retail, Healthcare enterprises — AI product engineering... | 25+ AI products in production combined with 3,000+ global engineers — enterprise AI scale without the big-four overhead | 4.1 | Full comparison |
| Iflexion | ML newcomers, AI strategy and scoping first. | Consulting-first model ensures the ML problem is correctly defined before engineering investment begins | 4.0 | Full comparison |
| Itransition | EU-operating enterprises, GDPR/EU AI Act-compliant ML. | EU regulatory compliance depth for ML — GDPR-aligned data architecture and EU AI Act readiness built into delivery | 4.0 | Full comparison |
| DataToBiz | Startups taking an ML idea to market-ready delivery. | Product-oriented ML delivery — combines AI strategy with full-cycle engineering to produce launchable products, not just models | 4.0 | Full comparison |
| BairesDev | Enterprises and scale-ups, fast teams, US time-zone aligned. | Latin American engineering delivery with US time-zone alignment — faster team ramp than Asian offshore with significant rate advantage versus US onshore | 4.0 | Full comparison |
| Andersen Lab | Enterprises, large-scale ML, Fortune-500 references, EU footprint. | Named client references including Siemens, S&P Global, and Ryanair — enterprise ML track record at the highest scale | 4.0 | Full comparison |
| Intuz | SMBs, US-headquartered AI/ML at accessible rates. | 1,700+ delivered projects for SMBs — the broadest SMB ML delivery track record in this list | 3.9 | Full comparison |
| Tredence | Fortune 500 enterprises, AI analytics and supply-chain ML. | Large specialised analytics and AI firm — enterprise supply chain ML and CX analytics depth with Fortune 500 client delivery track record | 3.9 | Full comparison |
| Codiant | Budget-conscious orgs, end-to-end ML delivery. | Cost-efficient end-to-end ML delivery covering all phases — discovery, build, integration, and optimisation — in a single engagement | 3.9 | Full comparison |
| GlobalLogic (Hitachi) | Global enterprises, massive-scale MLOps, Hitachi-backed. | Hitachi Group backing with 27,000 engineers — the scale and compliance posture of a major industrial conglomerate applied to enterprise ML | 3.9 | Full comparison |
| EPAM Systems | Global enterprises, complex AI products, governance at scale. | AI-native engineering practice at 50,000-person scale — the broadest talent pool and delivery capacity of any firm on this list | 3.8 | Full comparison |
| Cognizant | Fortune 500 enterprises, multi-year AI transformation programmes. | One of the world's largest AI & Analytics practices — Fortune 500 industry vertical depth and compliance credentials at 350,000-person delivery scale | 3.8 | Full comparison |
| Accenture | Global enterprises, governed GenAI and agentic AI at... | Accenture's global AI practice applies consulting strategy, industry domain expertise, and engineering delivery at 700,000-person scale — designed exclusively for enterprise | 3.8 | Full comparison |
| DataRobot | Enterprise data-science teams, governed AutoML platform. | Platform-driven ML — DataRobot's AutoML engine and MLOps governance layer enable internal data science teams to build and manage models at scale without per-project custom development | 3.8 | Full comparison |
Oxagile FAQ
What is Oxagile?
Oxagile is a software and AI development company founded in 2005 and headquartered in Minsk, Belarus, with 250–999 employees. The firm offers AI software development services with a focus on data-driven solutions for digital transformation. Oxagile is recognised for connected care AI in healthcare, computer vision in media and retail, and custom ML systems for enterprise clients across multiple verticals.
How much does Oxagile charge?
Oxagile uses fixed project, t&m, dedicated team pricing. Minimum engagement starts at $20K. A discovery call is required to get project-specific quotes.
What tech stack does Oxagile use?
Oxagile works with Python, TensorFlow, OpenCV, Keras, AWS, GCP, Scikit-learn, ONNX. Primary industries served include Healthcare & Life Sciences, Media & Entertainment, Financial Services, Manufacturing & Industrial, Retail & E-commerce.
Is Oxagile right for enterprise?
Healthcare/media/retail enterprises, cost-effective Eastern European ML. 250–999 team size. Key consideration: Belarus-based delivery carries geopolitical risk and potential regulatory complications for some enterprises.
What are the best Oxagile alternatives?
The best alternatives to Oxagile depend on your use case. Top options are:
- Tensorway: boutique ml depth, with access to the 25-year enterprise delivery experience of its parent company — a rare combination in the ml services market
- LeewayHertz: among the earliest boutique firms to build a structured genai delivery framework — deep llm orchestration and rag pipeline experience
- Scopic: engineers custom ml architectures from the ground up — not fine-tuned wrappers — with 20 years of production delivery discipline
Compare Oxagile with other Machine Learning Development companies
Oxagile vs Tensorway Oxagile vs LeewayHertz Oxagile vs Scopic Oxagile vs InData Labs Oxagile vs DATAFOREST Oxagile vs Forte Group Oxagile vs RTS Labs Oxagile vs Quantiphi Oxagile vs N-iX Oxagile vs Miquido Oxagile vs Algoscale Oxagile vs STX Next Oxagile vs Intellias Oxagile vs ScienceSoft Oxagile vs Simform Oxagile vs Softeq Oxagile vs Aimprosoft Oxagile vs Uvik Software Oxagile vs Ciklum Oxagile vs Iflexion Oxagile vs Itransition Oxagile vs DataToBiz Oxagile vs BairesDev Oxagile vs Andersen Lab Oxagile vs Intuz Oxagile vs Tredence Oxagile vs Codiant Oxagile vs GlobalLogic (Hitachi) Oxagile vs EPAM Systems Oxagile vs Cognizant Oxagile vs Accenture Oxagile vs DataRobot