Scopic
A 20-year-old distributed software company with 1,000+ engineers building custom ML systems in transportation, healthcare, manufacturing, and finance.
Founded 2006 | Marlborough, MA, USA (distributed) | 1,000–2,000 employees | Last updated: July 2026
custom-mldeep-learningcomputer-visionpredictive-analyticsdata-engineering
What is Scopic?
Scopic is a globally distributed software development company headquartered in Marlborough, Massachusetts, with a remote-first team of 1,000+ engineers spanning 50+ countries. Founded in 2006, Scopic builds custom ML systems using TensorFlow, neural networks, and PyTorch for clients in transportation, healthcare, manufacturing, and finance. The distributed model keeps overhead low while providing senior engineering talent across multiple time zones. Scopic has published ML case studies in medical imaging, predictive maintenance, and financial risk modelling.
Scopic was founded in 2006 and is headquartered in Marlborough, MA, USA (distributed). The firm employs 1,000–2,000 people and works primarily with clients in Healthcare, Manufacturing, Fintech, Logistics, SaaS sectors. Its primary differentiator is: 20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk.
Scopic tech stack and services
PythonTensorFlowPyTorchScikit-learnNeural NetworksOpenCVAWSGCPDockerPostgreSQL
| Service area | Details |
|---|---|
| Medical imaging analysis using CNN-based deep learning models | Available for Healthcare, Manufacturing, Fintech, Logistics, SaaS clients |
| Predictive maintenance systems for manufacturing equipment | Available for Healthcare, Manufacturing, Fintech, Logistics, SaaS clients |
| Financial risk models for credit scoring and fraud detection | Available for Healthcare, Manufacturing, Fintech, Logistics, SaaS clients |
| Custom neural networks for transportation route optimisation | Available for Healthcare, Manufacturing, Fintech, Logistics, SaaS clients |
| Data science pipeline engineering for SaaS analytics products | Available for Healthcare, Manufacturing, Fintech, Logistics, SaaS clients |
Scopic use cases
Short answer: Scopic is best suited for companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries.
| Use case | Industries | Approach |
|---|---|---|
| Medical imaging analysis using CNN-based deep learning models | Healthcare, Manufacturing | Python, TensorFlow |
| Predictive maintenance systems for manufacturing equipment | Healthcare, Manufacturing | Python, TensorFlow |
| Financial risk models for credit scoring and fraud detection | Healthcare, Manufacturing | Python, TensorFlow |
| Custom neural networks for transportation route optimisation | Healthcare, Manufacturing | Python, TensorFlow |
| Data science pipeline engineering for SaaS analytics products | Healthcare, Manufacturing | Python, TensorFlow |
Scopic pricing
Short answer: Scopic uses a dedicated team, t&m, fixed project pricing approach. Minimum engagement starts at $30K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
| Fixed project | From $30K | Well-defined scope |
Scopic does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
Scopic pros and cons
| Advantages | Things to consider |
|---|---|
| +20-year track record with 1,000+ distributed engineers provides delivery confidence | -Fully distributed model requires strong async communication discipline from client teams |
| +Published ML case studies in healthcare imaging, manufacturing maintenance, and financial risk | -ML is one of several practice areas — not a pure-play AI specialist firm |
| +Remote-first model provides access to senior talent at competitive rates | -Less emphasis on cutting-edge deep learning research than boutique ML-only firms |
| +Wide range of ML use cases covered across multiple industries | |
| +Flexible engagement: dedicated team, T&M, or fixed project scope |
Scopic vs alternatives
How Scopic compares to the other top Machine Learning Development companies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| InData Labs | Mid-market companies needing custom production-grade ML systems with... | Pure-play data science boutique with 4.9/5 Clutch rating across 18 independent reviews and documented post-launch iteration model | 4.8 | Full comparison |
| Tensorway | Mid-market and enterprise clients needing production-grade computer vision... | Deep learning specialist backed by Anadea's 25-year delivery heritage, with a dedicated computer vision practice covering detection, segmentation, and video analytics | 4.6 | Full comparison |
| Simform | AWS-first companies needing production ML systems with cloud-native... | AWS Premier Partner with 200+ ML engineers and 4.8/5 Clutch rating across 82 verified reviews — one of the most independently validated firms in this niche | 4.5 | Full comparison |
| Blackthorn Vision | Mid-market companies in healthcare, fintech, or industrial automation... | Published case studies across healthcare and fintech ML with a documented data science lifecycle and accessible $20K minimum engagement | 4.4 | Full comparison |
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| N-iX | Enterprises with complex data infrastructure needing MLOps expertise... | Named Fortune 500 MLOps deployments at Bosch, Gogo, and Fluke with 2,000+ engineers and a data-infrastructure-first ML approach | 3.9 | Full comparison |
| Intellias | Product companies and enterprises needing ML integrated into... | Product-engineering-first approach to ML with a dedicated MLOps practice and documented automotive and fintech AI delivery experience | 3.8 | Full comparison |
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| Devox Software | EU, UK, and US clients needing cost-efficient Python... | High client retention rate (82% long-term partnerships) with Python-native ML focus for finance and retail use cases | 3.7 | Full comparison |
| Intuz | US-based companies needing a San Francisco-headquartered AI partner... | San Francisco-headquartered AI firm founded in 2008 with ML and AI agent development alongside standard ML model development | 3.7 | Full comparison |
| Softeq | Enterprise companies with hardware, IoT, or embedded systems... | Houston-based enterprise firm with unique strength in ML for IoT and hardware-connected AI applications alongside Microsoft and AWS partnerships | 3.7 | Full comparison |
| Itransition | Enterprise organisations needing ML consulting and implementation integrated... | 25-year global firm with 3,000+ engineers across 40+ countries offering ML consulting within enterprise technology programmes | 3.7 | Full comparison |
| ELEKS | Enterprise and Fortune 500 companies needing a long-established... | 35-year software engineering heritage with 1,000+ delivered data-driven projects and US presence in Chicago for North American enterprise clients | 3.6 | Full comparison |
| Avenga | Global corporations needing a large-scale European technology partner... | 6,000-person global consultancy with AWS Advanced Partnership and 20+ certified cloud ML deployments across 16 countries and 44 delivery locations | 3.6 | Full comparison |
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| Ciklum | Global enterprises seeking AI features embedded in large-scale... | 4,000-person Experience Engineering firm with 250+ enterprise clients and generative AI delivery integrated into large product programmes | 3.6 | Full comparison |
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| Codiant | Startups and mid-market companies on five continents needing... | Yash Technologies subsidiary with ISO 9001 and 27001 certifications, multi-continent delivery, and 700+ completed projects for 200+ active clients | 3.6 | Full comparison |
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| EPAM Systems | Large enterprises needing ML within large-scale platform engineering... | Publicly traded 62,000-person firm with proprietary EPAM DIAL AI orchestration platform and AI transformation engineering positioning for global enterprises | 3.5 | Full comparison |
| Accenture | Global enterprise and government organisations needing AI strategy,... | World's largest consulting firm with 700,000+ employees, government-scale AI governance capability, and a dedicated AI transformation practice | 3.5 | Full comparison |
| Cognizant | Global enterprises modernising legacy data systems and needing... | 330,000-person IT services firm combining ML engineering with legacy data modernisation for global enterprise digital transformation programmes | 3.5 | Full comparison |
Scopic FAQ
What is Scopic?
Scopic is a globally distributed software development company headquartered in Marlborough, Massachusetts, with a remote-first team of 1,000+ engineers spanning 50+ countries. Founded in 2006, Scopic builds custom ML systems using TensorFlow, neural networks, and PyTorch for clients in transportation, healthcare, manufacturing, and finance. The distributed model keeps overhead low while providing senior engineering talent across multiple time zones. Scopic has published ML case studies in medical imaging, predictive maintenance, and financial risk modelling.
How much does Scopic charge?
Scopic uses dedicated team, t&m, fixed project pricing. Minimum engagement starts at $30K. A discovery call is required to get project-specific quotes.
What tech stack does Scopic use?
Scopic works with Python, TensorFlow, PyTorch, Scikit-learn, Neural Networks, OpenCV, AWS, GCP, Docker, PostgreSQL. Primary industries served include Healthcare, Manufacturing, Fintech, Logistics, SaaS.
Is Scopic right for enterprise?
Companies needing senior ML engineers at competitive rates with distributed team flexibility and published case studies across multiple industries. 1,000–2,000 team size. Key consideration: Fully distributed model requires strong async communication discipline from client teams.
What are the best Scopic alternatives?
The best alternatives to Scopic depend on your use case. Top options are:
- InData Labs: pure-play data science boutique with 4.9/5 clutch rating across 18 independent reviews and documented post-launch iteration model
- Tensorway: deep learning specialist backed by anadea's 25-year delivery heritage, with a dedicated computer vision practice covering detection, segmentation, and video analytics
- Simform: aws premier partner with 200+ ml engineers and 4.8/5 clutch rating across 82 verified reviews — one of the most independently validated firms in this niche
Compare Scopic with other Machine Learning Development companies
Scopic vs InData Labs Scopic vs Tensorway Scopic vs Simform Scopic vs Blackthorn Vision Scopic vs Codiste Scopic vs DataRoot Labs Scopic vs *instinctools Scopic vs Neoteric Scopic vs MobiDev Scopic vs Leobit Scopic vs STX Next Scopic vs LeewayHertz Scopic vs ScienceSoft Scopic vs Fractal Analytics Scopic vs Acropolium Scopic vs Iflexion Scopic vs N-iX Scopic vs Intellias Scopic vs Oxagile Scopic vs Innowise Scopic vs Appinventiv Scopic vs Devox Software Scopic vs Intuz Scopic vs Softeq Scopic vs Itransition Scopic vs ELEKS Scopic vs Avenga Scopic vs DataArt Scopic vs Ciklum Scopic vs Sigmoidal Scopic vs Codiant Scopic vs GlobalLogic Scopic vs BairesDev Scopic vs DataRobot Scopic vs EPAM Systems Scopic vs Accenture Scopic vs Cognizant
Last reviewed: July 2026. Verify all details directly with Scopic before making a decision.