10Pearls
AI-native engineering firm with 1,400+ experts recognized four times on CRN Solution Provider 500.
Founded 2004 | Vienna, VA, USA | 1,400+ employees
custom-mlml-consultinggenerative-aidata-engineeringpredictive-analytics
What is 10Pearls?
10Pearls is an AI-powered digital engineering company founded in 2004 and headquartered in Vienna, Virginia, in the Washington DC metro area. The company employs 1,400+ experts across North America, Latin America, Europe, and South Asia, and has been recognized four consecutive times on the CRN Solution Provider 500 list for enterprise AI delivery. 10Pearls serves enterprise and government clients in healthcare, financial services, and logistics with a focus on ML, cloud architecture, and cybersecurity-aware AI development.
10Pearls was founded in 2004 and is headquartered in Vienna, VA, USA. The firm employs 1,400+ people and works primarily with clients in healthcare, financial services, government, retail, logistics sectors. Its primary differentiator is: AI-native engineering culture with four CRN Solution Provider 500 recognitions and 1,400+ experts spanning North America and LATAM for enterprise AI programmes.
10Pearls tech stack and services
PythonTensorFlowPyTorchAWS SageMakerAzure MLOpenAIDockerKubernetesApache SparkTerraform
| Service area |
|---|
| Custom ML Development |
| ML Consulting |
| Generative AI |
| Data Engineering |
| Predictive Analytics |
10Pearls use cases
Short answer: 10Pearls is best suited for US enterprises and government contractors, AI-native, LATAM delivery.
| Use case |
|---|
| Federal government AI programme delivery with security clearance-compatible development practices |
| Healthcare ML development for clinical analytics under HIPAA constraints |
| Financial services ML for fraud detection and regulatory reporting automation |
| Predictive analytics platform build for logistics optimization |
| Generative AI integration into enterprise knowledge management or internal tooling |
10Pearls pricing
Short answer: 10Pearls uses a fixed project, dedicated team, t&m pricing approach. Minimum engagement starts at $30K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $30K | Well-defined scope |
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| T&M | Variable; depends on team size | Large programmes or team augmentation |
10Pearls does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
10Pearls pros and cons
| Advantages | Things to consider |
|---|---|
| +CRN Solution Provider 500 recognition (four times) independently validates enterprise AI delivery track record | -Less specialist ML boutique depth for highly complex model architecture challenges |
| +Washington DC metro HQ well suited for US federal government ML programmes | -Government and healthcare focus means less consumer-facing ML or retail AI breadth |
| +LATAM delivery centers enable nearshore agility in US time zones at competitive rates | -Minimum engagement ($30K) is on the higher end for US-based firms of this size |
| +AI-native culture — ML is embedded in the engineering culture, not a separate practice | |
| +Cybersecurity-aware AI development important for government and healthcare buyers |
10Pearls vs alternatives
How 10Pearls 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 |
| Oxagile | Media, AdTech, sports — video ML, 20+ years... | 20+ years of video domain expertise uniquely positions Oxagile for ML use cases involving video understanding, visual search, and real-time video analytics | 3.8 | 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 |
| 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 |
10Pearls FAQ
What is 10Pearls?
10Pearls is an AI-powered digital engineering company founded in 2004 and headquartered in Vienna, Virginia, in the Washington DC metro area. The company employs 1,400+ experts across North America, Latin America, Europe, and South Asia, and has been recognized four consecutive times on the CRN Solution Provider 500 list for enterprise AI delivery. 10Pearls serves enterprise and government clients in healthcare, financial services, and logistics with a focus on ML, cloud architecture, and cybersecurity-aware AI development.
How much does 10Pearls charge?
10Pearls uses fixed project, dedicated team, t&m pricing. Minimum engagement starts at $30K. A discovery call is required to get project-specific quotes.
What tech stack does 10Pearls use?
10Pearls works with Python, TensorFlow, PyTorch, AWS SageMaker, Azure ML, OpenAI, Docker, Kubernetes, Apache Spark, Terraform. Primary industries served include healthcare, financial services, government, retail, logistics.
Is 10Pearls right for enterprise?
US enterprises and government contractors, AI-native, LATAM delivery. 1,400+ team size. Key consideration: Less specialist ML boutique depth for highly complex model architecture challenges.
What are the best 10Pearls alternatives?
The best alternatives to 10Pearls 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 10Pearls with other Machine Learning Development companies
10Pearls vs Tensorway 10Pearls vs LeewayHertz 10Pearls vs InData Labs 10Pearls vs HatchWorks AI 10Pearls vs STX Next 10Pearls vs Tredence 10Pearls vs Addepto 10Pearls vs DataForest 10Pearls vs Forte Group 10Pearls vs Binariks 10Pearls vs Softeq 10Pearls vs Markovate 10Pearls vs ScienceSoft 10Pearls vs Miquido 10Pearls vs Simform 10Pearls vs Intuz 10Pearls vs Scopic 10Pearls vs N-iX 10Pearls vs Oxagile 10Pearls vs Innowise 10Pearls vs Intellectsoft 10Pearls vs DataRoot Labs 10Pearls vs Itransition 10Pearls vs Coherent Solutions 10Pearls vs Iflexion 10Pearls vs Appinventiv 10Pearls vs Avenga 10Pearls vs BairesDev 10Pearls vs Turing 10Pearls vs EPAM Systems