ScienceSoft
A 35-year-old McKinney, Texas IT firm with Microsoft Gold and AWS partner certifications and ML for manufacturing, healthcare, and oil & gas.
What is ScienceSoft?
ScienceSoft is a global IT services company founded in 1989 and headquartered in McKinney, Texas, with 700+ employees and delivery centres in Eastern Europe and the Americas. The firm's machine learning practice focuses on custom ML solutions for manufacturing, healthcare, and oil & gas industries, with a 35-year IT track record across 20+ countries. ScienceSoft's ML engineers design and implement models for demand forecasting, quality prediction, medical diagnostics, and production optimisation. The company holds Microsoft Gold Partnership and AWS Partner certifications.
ScienceSoft was founded in 1989 and is headquartered in McKinney, TX, USA. The firm employs 700–1,000 people and works primarily with clients in Manufacturing, Healthcare, SaaS, Logistics, Fintech sectors. Its primary differentiator is: 35-year IT firm with Microsoft Gold and AWS partner certifications and documented vertical depth in manufacturing, healthcare, and oil & gas ML.
ScienceSoft tech stack and services
| Service area | Details |
|---|---|
| Demand forecasting and production optimisation ML for manufacturing plants | Available for Manufacturing, Healthcare, SaaS, Logistics, Fintech clients |
| Clinical decision support ML for healthcare providers and hospital systems | Available for Manufacturing, Healthcare, SaaS, Logistics, Fintech clients |
| Predictive maintenance for oil & gas equipment and industrial infrastructure | Available for Manufacturing, Healthcare, SaaS, Logistics, Fintech clients |
| Quality inspection ML for industrial production processes | Available for Manufacturing, Healthcare, SaaS, Logistics, Fintech clients |
| Supply chain optimisation analytics for logistics and distribution companies | Available for Manufacturing, Healthcare, SaaS, Logistics, Fintech clients |
ScienceSoft use cases
Short answer: ScienceSoft is best suited for manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials.
| Use case | Industries | Approach |
|---|---|---|
| Demand forecasting and production optimisation ML for manufacturing plants | Manufacturing, Healthcare | Python, Scikit-learn |
| Clinical decision support ML for healthcare providers and hospital systems | Manufacturing, Healthcare | Python, Scikit-learn |
| Predictive maintenance for oil & gas equipment and industrial infrastructure | Manufacturing, Healthcare | Python, Scikit-learn |
| Quality inspection ML for industrial production processes | Manufacturing, Healthcare | Python, Scikit-learn |
| Supply chain optimisation analytics for logistics and distribution companies | Manufacturing, Healthcare | Python, Scikit-learn |
ScienceSoft pricing
Short answer: ScienceSoft uses a fixed project, dedicated team, t&m pricing approach. Minimum engagement starts at $50K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $50K | Well-defined scope |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| Time & materials | Variable; depends on team size | Large programmes or team augmentation |
ScienceSoft pros and cons
| Advantages | Things to consider |
|---|---|
| +35-year delivery track record provides confidence for regulated industry procurement requirements | -ML is one of many IT service lines — not a pure-play AI specialist firm |
| +Microsoft Gold and AWS Partner certifications verify cloud ML deployment credentials | -Primary vertical focus on manufacturing and healthcare may not serve other sectors equally well |
| +Deep manufacturing, healthcare, and oil & gas ML vertical expertise with named case studies | -Higher minimum engagement than boutique ML alternatives at similar quality tier |
| +700+ employees provide delivery capacity for large concurrent enterprise programmes | |
| +US Texas HQ for North American enterprise client engagement and account management |
ScienceSoft vs alternatives
How ScienceSoft 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 |
| Codiste | Startups and mid-market companies needing full ML lifecycle... | AI-first engineering firm with explicit MLOps focus and generative AI capability alongside classical ML model development | 4.3 | Full comparison |
| DataRoot Labs | European and Israeli companies needing a structured ML... | Structured AI R&D methodology with formal experiment cycles serving European and Israeli mid-market clients | 4.2 | Full comparison |
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| Scopic | Companies needing senior ML engineers at competitive rates... | 20-year distributed firm with 1,000+ remote engineers and published ML case studies in healthcare, manufacturing, and financial risk | 3.8 | Full comparison |
| Iflexion | Enterprises needing a consulting-first ML partner to design... | 25-year enterprise IT firm with a consulting-led ML practice that evaluates feasibility and designs data strategy before implementation begins | 3.8 | Full comparison |
| 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 |
| Oxagile | Media, sports, and AdTech companies needing AI and... | 20-year video technology specialist with strong computer vision and video analytics ML capability for media, sports, and AdTech clients | 3.8 | Full comparison |
| Innowise | Banks, healthcare operators, and agricultural businesses needing ML... | 1,200-engineer Eastern European firm with documented banking, healthcare, and agriculture ML delivery from Poland and UAE offices | 3.8 | Full comparison |
| Appinventiv | Enterprise and mid-market companies needing ML features integrated... | 200+ dedicated ML experts within a 1,600+ person firm delivering ML at scale within mobile and enterprise product development | 3.7 | Full comparison |
| 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 |
| DataArt | Mid-market and enterprise companies in finance, healthcare, or... | 29-year global engineering firm with 6,000+ specialists and a flat structure providing direct access to senior ML engineers on client projects | 3.6 | Full comparison |
| 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 |
| Sigmoidal | Financial services and healthcare companies with internal ML... | Specialist ML staff augmentation firm placing expert data scientists and ML engineers into client teams with financial services industry focus | 3.6 | Full comparison |
| 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 |
| GlobalLogic | Fortune 500 enterprises needing large-scale MLOps implementation within... | Hitachi-owned 30,000-person product engineering firm with MLOps and AI-Powered SDLC for Fortune 500 clients and industrial AI access via Hitachi ecosystem | 3.5 | Full comparison |
| BairesDev | US-based companies needing culturally aligned nearshore ML engineers... | Latin America nearshore ML specialist with 4,000+ engineers and US timezone alignment for flexible staff augmentation and project delivery | 3.5 | Full comparison |
| DataRobot | Enterprises wanting to reduce ML engineering bottlenecks with... | Enterprise AutoML platform that automates model building and deployment — a software product with professional services, not a custom development services firm | 3.5 | Full comparison |
| 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 |
ScienceSoft FAQ
What is ScienceSoft?
ScienceSoft is a global IT services company founded in 1989 and headquartered in McKinney, Texas, with 700+ employees and delivery centres in Eastern Europe and the Americas. The firm's machine learning practice focuses on custom ML solutions for manufacturing, healthcare, and oil & gas industries, with a 35-year IT track record across 20+ countries. ScienceSoft's ML engineers design and implement models for demand forecasting, quality prediction, medical diagnostics, and production optimisation. The company holds Microsoft Gold Partnership and AWS Partner certifications.
How much does ScienceSoft charge?
ScienceSoft uses fixed project, dedicated team, t&m pricing. Minimum engagement starts at $50K. A discovery call is required to get project-specific quotes.
What tech stack does ScienceSoft use?
ScienceSoft works with Python, Scikit-learn, TensorFlow, PyTorch, Azure ML, AWS SageMaker, SQL Server, Power BI, MLflow, Docker. Primary industries served include Manufacturing, Healthcare, SaaS, Logistics, Fintech.
Is ScienceSoft right for enterprise?
Manufacturing, healthcare, and oil & gas companies needing a long-established US-headquartered ML partner with Microsoft and AWS credentials. 700–1,000 team size. Key consideration: ML is one of many IT service lines — not a pure-play AI specialist firm.
What are the best ScienceSoft alternatives?
The best alternatives to ScienceSoft 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 ScienceSoft with other Machine Learning Development companies
Last reviewed: July 2026. Verify all details directly with ScienceSoft before making a decision.