Oxagile
New York-based ML firm with 20+ years of video domain expertise for media, AdTech, and sports AI.
Founded 2005 | New York, NY, USA | 250–500 employees
custom-mlcomputer-visiondeep-learningdata-engineeringml-consulting
What is Oxagile?
Oxagile is a custom software development vendor founded in 2005 and headquartered in New York, with delivery centers in Eastern Europe. The company has 20+ years of video domain expertise and has applied machine learning to video understanding, visual search, and real-time video analytics for clients in media, advertising, sports, and retail. Oxagile's ML practice is particularly strong in use cases where video processing is the core data source.
Oxagile was founded in 2005 and is headquartered in New York, NY, USA. The firm employs 250–500 people and works primarily with clients in media, advertising, retail, sports, healthcare sectors. Its primary differentiator is: 20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics.
Oxagile tech stack and services
TensorFlowPyTorchOpenCVPythonAWSGCPFFmpegNVIDIA CUDADockerKubernetesWebRTC
| Service area |
|---|
| Custom ML Development |
| Computer Vision |
| Deep Learning |
| Data Engineering |
| ML Consulting |
Oxagile use cases
Short answer: Oxagile is best suited for Media, AdTech, sports — video ML, 20+ years video expertise.
| Use case |
|---|
| Video content analysis ML for content moderation, tagging, or recommendation |
| Computer vision model development for sports performance analysis |
| AdTech ML development for audience classification and real-time bidding optimization |
| Visual search ML for e-commerce product discovery using image input |
| Real-time video analytics system development for retail foot traffic or security applications |
Oxagile pricing
Short answer: Oxagile uses a fixed project, t&m, dedicated team 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 |
| 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 |
|---|---|
| +20+ years of video technology expertise is a genuinely rare differentiator in the ML market | -Video-first specialization means less breadth for non-video ML use cases |
| +NVIDIA CUDA expertise for GPU-accelerated video ML inference at production scale | -Less generative AI LLM tooling depth compared to AI-first firms |
| +AdTech ML specialization for audience targeting and real-time bidding optimization models | -Limited public case studies outside media, AdTech, and sports verticals |
| +WebRTC and live video stream processing capability alongside batch video analysis | |
| +Eastern European delivery with New York client-facing presence |
Oxagile vs alternatives
How Oxagile compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Dedicated ML boutique, strategy through production MLOps. | ML-only focus with a dedicated specialist team backed by 25 years of the parent company software delivery infrastructure — unusually deep for a firm of this size | 4.8 | Full comparison |
| LeewayHertz | Enterprises, end-to-end AI delivery, Fortune 500 clients. | Product-centric AI delivery culture with verified Fortune 500 client references including ESPN, Siemens, and 3M — now operating within The Hackett Group | 4.0 | Full comparison |
| InData Labs | Mid-market orgs, complex ML, deep data-science expertise. | Pure-play ML boutique with a measurably higher specialist-to-generalist ratio than typical service firms, confirmed by Clutch as a top AI service provider | 4.5 | Full comparison |
| HatchWorks AI | Companies wanting AI-native, generative-AI-embedded delivery. | Clutch #1 AI Services Company with a proprietary Generative Driven Development methodology claimed to reduce delivery time by 30–50% (per company website; independently unverifiable) | 4.4 | Full comparison |
| STX Next | Orgs needing ML operationalized in Python-native systems. | Europe's largest Python-specialist firm uniquely positioned to embed ML into production software without the integration friction that plagues pure-play ML boutiques | 4.3 | Full comparison |
| Tredence | Enterprises, last-mile ML adoption, supply chain and retail. | Industry-specific AI accelerators and a proven focus on last-mile ML adoption, closing the execution gap between data science output and real business value | 4.3 | Full comparison |
| Addepto | Finance, energy, retail — bespoke ML with pipeline... | End-to-end AI/ML delivery with particular sector depth in financial services and energy — industries that require compliance sophistication alongside technical capability | 4.2 | Full comparison |
| DataForest | Data-first companies, robust engineering foundation for ML. | Data engineering-first approach builds pipeline and data quality foundations before model development, addressing the root cause of most ML project failures | 4.2 | Full comparison |
| Forte Group | Orgs wanting Tier-1 rigor, specialist agility, roadmap to... | Structured AI service lines with Tier 1 delivery rigor and specialist consultancy agility — serving organizations that need both without enterprise-tier pricing | 4.1 | Full comparison |
| Binariks | Healthcare, fintech, insurance — compliance-first ML engineering. | Compliance-first ML engineering for regulated industries — governance and audit trails are built in from the architecture stage, not retrofitted after launch | 4.1 | Full comparison |
| Softeq | Hardware and industrial companies, edge ML on embedded... | Unique capability to combine hardware design expertise with ML engineering, deploying models at the edge where cloud-only ML firms cannot operate | 4.1 | Full comparison |
| Markovate | Retail, travel, fitness — recommendation engines, 300+ projects. | 300+ delivered projects spanning recommendation systems, computer vision, and dynamic pricing, with deeper consumer-facing ML specialization than most comparably sized firms | 4.0 | Full comparison |
| ScienceSoft | Established enterprises, 35+ years, stable US vendor. | 35+ years of enterprise delivery experience with a mature ML practice — providing compliance readiness, institutional knowledge, and process maturity rare in younger ML-focused competitors | 4.0 | Full comparison |
| Miquido | Product teams, ML in polished products, Google-certified. | Google-certified AI/ML capability paired with strong product design — clients receive ML that works inside well-crafted user experiences, not bolted-on algorithms | 4.0 | Full comparison |
| Simform | Industrial and enterprise, cloud-native AWS ML at scale. | AWS Premier Partner with 1,000+ engineers and documented depth in industrial IoT ML — connecting physical sensor streams to cloud ML inference at production scale | 3.9 | Full comparison |
| Intuz | SMBs, fixed-price discovery, 1,700+ projects. | 1,700+ project track record with a discovery-first engagement model making enterprise-grade ML accessible to SMBs through risk-reduced fixed-price POC phases | 3.9 | Full comparison |
| Scopic | Orgs wanting custom ML, 20+ years, strong computer... | 20+ years as a distributed software company gives Scopic strong custom ML engineering discipline with confirmed production deployments across transportation and healthcare | 3.9 | Full comparison |
| N-iX | Enterprises, large-scale Eastern-Europe ML engineering capacity. | 2,400+ engineers with deep specialization in scalable AI architectures, able to field large dedicated teams for complex multi-year ML programmes at competitive Eastern European rates | 3.9 | Full comparison |
| Innowise | Banking, agriculture, healthcare — compliance-aware ML. | Cross-vertical ML delivery with documented case studies in banking automation, agricultural forecasting, and healthcare diagnostics — unusual breadth across regulated industries | 3.9 | Full comparison |
| Intellectsoft | Fintech, healthcare, construction — ML in enterprise ecosystems. | Palo Alto HQ with 10 global delivery offices combining US-based account management with competitive Eastern European delivery rates for enterprise ML programmes | 3.8 | Full comparison |
| DataRoot Labs | Startups and scale-ups, AI strategy plus execution, accessible. | One of Ukraine's most recognized ML consultancies — combining strategy-level AI advisory with hands-on engineering, a combination rare at this team size and price point | 3.8 | Full comparison |
| Itransition | Enterprises, ML in legacy systems, 25+ years delivery. | 25+ years of enterprise software delivery with five dedicated R&D labs, giving clients a mature delivery operation with advanced ML research support at competitive rates | 3.9 | Full comparison |
| 10Pearls | US enterprises and government contractors, AI-native, LATAM delivery. | AI-native engineering culture with four CRN Solution Provider 500 recognitions and 1,400+ experts spanning North America and LATAM for enterprise AI programmes | 3.8 | Full comparison |
| Coherent Solutions | Microsoft-stack enterprises, #1 Twin Cities IT firm. | Ranked #1 IT consulting firm in the Twin Cities five times in six years with 2,000+ engineers across 10 development centers, offering enterprise ML at competitive rates | 3.8 | Full comparison |
| Iflexion | US orgs, ML within custom enterprise software systems. | 25 years of enterprise software delivery with 850+ professionals embedding ML into complete systems rather than delivering standalone models that require separate integration work | 3.7 | Full comparison |
| Appinventiv | Global businesses, mobile-first ML, five-continent delivery. | 1,600+ specialists with a mobile-first AI approach and global footprint delivering 1,000+ digital assets with embedded ML — strong for consumer-facing AI product work | 3.8 | Full comparison |
| Avenga | Telco, banking, automotive enterprises — 6,000+ engineer scale. | 6,000+ specialists across 44 delivery centers formed through PE-backed acquisitions, providing enterprise-scale AI delivery capacity — though cultural integration across legacy entities is ongoing | 3.7 | Full comparison |
| BairesDev | Companies wanting rapid ML scale-up, LATAM nearshore, US... | 4,000+ ML-capable LATAM engineers in US time zones with 1,200+ completed projects, enabling rapid scale-up for organizations that need to grow their ML capacity fast | 3.7 | Full comparison |
| Turing | Teams needing pre-vetted senior ML developers, staff augmentation. | AI-powered vetting platform screening 3M+ global ML developers to place the top 1% directly in client engineering teams at rates competitive with US in-house hiring | 3.7 | Full comparison |
| EPAM Systems | Large enterprises, Fortune 500 scale, global compliance. | 62,000+ engineers across 50+ countries delivering ML inside a full-service technology engineering operation — unmatched scale and compliance depth for global enterprise AI programmes | 3.9 | Full comparison |
Oxagile FAQ
What is Oxagile?
Oxagile is a custom software development vendor founded in 2005 and headquartered in New York, with delivery centers in Eastern Europe. The company has 20+ years of video domain expertise and has applied machine learning to video understanding, visual search, and real-time video analytics for clients in media, advertising, sports, and retail. Oxagile's ML practice is particularly strong in use cases where video processing is the core data source.
How much does Oxagile charge?
Oxagile uses fixed project, t&m, dedicated team pricing. Minimum engagement starts at $25K. A discovery call is required to get project-specific quotes.
What tech stack does Oxagile use?
Oxagile works with TensorFlow, PyTorch, OpenCV, Python, AWS, GCP, FFmpeg, NVIDIA CUDA, Docker, Kubernetes, WebRTC. Primary industries served include media, advertising, retail, sports, healthcare.
Is Oxagile right for enterprise?
Media, AdTech, sports — video ML, 20+ years video expertise. 250–500 team size. Key consideration: Video-first specialization means less breadth for non-video ML use cases.
What are the best Oxagile alternatives?
The best alternatives to Oxagile depend on your use case. Top options are:
- Tensorway: ml-only focus with a dedicated specialist team backed by 25 years of the parent company software delivery infrastructure — unusually deep for a firm of this size
- LeewayHertz: product-centric ai delivery culture with verified fortune 500 client references including espn, siemens, and 3m — now operating within the hackett group
- InData Labs: pure-play ml boutique with a measurably higher specialist-to-generalist ratio than typical service firms, confirmed by clutch as a top ai service provider
Compare Oxagile with other Machine Learning Development companies
Oxagile vs Tensorway Oxagile vs LeewayHertz Oxagile vs InData Labs Oxagile vs HatchWorks AI Oxagile vs STX Next Oxagile vs Tredence Oxagile vs Addepto Oxagile vs DataForest Oxagile vs Forte Group Oxagile vs Binariks Oxagile vs Softeq Oxagile vs Markovate Oxagile vs ScienceSoft Oxagile vs Miquido Oxagile vs Simform Oxagile vs Intuz Oxagile vs Scopic Oxagile vs N-iX Oxagile vs Innowise Oxagile vs Intellectsoft Oxagile vs DataRoot Labs Oxagile vs Itransition Oxagile vs 10Pearls Oxagile vs Coherent Solutions Oxagile vs Iflexion Oxagile vs Appinventiv Oxagile vs Avenga Oxagile vs BairesDev Oxagile vs Turing Oxagile vs EPAM Systems