DataRobot
AutoML and AI platform leader with platform-led consulting and $285M ARR — delivers production ML in under 90 days.
Founded 2012 | Boston, MA, USA | 863 employees | Last updated: July 2026
mlopscustom-mlai-strategypredictive-analytics
What is DataRobot?
DataRobot was founded in 2012 and is headquartered in Boston, Massachusetts, with 863 employees as of recent figures. It is the category-defining automated machine learning (AutoML) platform vendor with approximately $285M in annual recurring revenue and a $6.3B valuation. DataRobot's consulting and ML development services are platform-led — clients use its enterprise AI cloud to automate model selection, training, evaluation, and deployment — with Quickstart programmes designed to take clients from concept to production in under 90 days. Its value proposition is speed and repeatability: organisations that need ML models deployed quickly without building bespoke data science infrastructure benefit most from DataRobot's platform approach.
DataRobot was founded in 2012 and is headquartered in Boston, MA, USA. The firm employs 863 people and works primarily with clients in Financial Services, Healthcare, Retail / E-commerce, Manufacturing, Logistics sectors. Its primary differentiator is: Category-defining AutoML platform with $285M ARR — accelerates time-to-production ML without requiring a dedicated data science team.
DataRobot tech stack and services
AutoMLPythonAWSAzureGCPKubernetesSnowflakeDatabricksREST API
| Service area | Details |
|---|---|
| Rapid churn prediction and customer lifetime value modelling for enterprises without large data science teams | Available for Financial Services, Healthcare, Retail / E-commerce, Manufacturing, Logistics clients |
| Credit risk and fraud scoring deployment using pre-built financial services ML accelerators | Available for Financial Services, Healthcare, Retail / E-commerce, Manufacturing, Logistics clients |
| Demand forecasting and supply chain ML with Quickstart delivery in 90 days | Available for Financial Services, Healthcare, Retail / E-commerce, Manufacturing, Logistics clients |
| Manufacturing quality control predictive ML with automated model retraining on production drift | Available for Financial Services, Healthcare, Retail / E-commerce, Manufacturing, Logistics clients |
DataRobot use cases
Short answer: DataRobot is best suited for enterprises wanting rapid ML deployment via an enterprise AutoML platform rather than bespoke custom model development.
| Use case | Industries | Approach |
|---|---|---|
| Rapid churn prediction and customer lifetime value modelling for enterprises without large data science teams | Financial Services, Healthcare | AutoML, Python |
| Credit risk and fraud scoring deployment using pre-built financial services ML accelerators | Financial Services, Healthcare | AutoML, Python |
| Demand forecasting and supply chain ML with Quickstart delivery in 90 days | Financial Services, Healthcare | AutoML, Python |
| Manufacturing quality control predictive ML with automated model retraining on production drift | Financial Services, Healthcare | AutoML, Python |
DataRobot pricing
Short answer: DataRobot uses a fixed project, retainer pricing approach. Minimum engagement starts at $50K.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed project | From $50K | Well-defined scope |
| Retainer | Monthly rate; not public | Ongoing AI engineering |
DataRobot does not publish a public rate card. Contact them directly via their website to get project-specific pricing.
DataRobot pros and cons
| Advantages | Things to consider |
|---|---|
| +$285M ARR and $6.3B valuation validate large-scale enterprise adoption of the AutoML platform | -Platform lock-in: migrating away from DataRobot once production models are embedded requires significant re-engineering |
| +Quickstart programme delivers production ML in under 90 days — fastest time-to-value in this review for standard use cases | -AutoML approach trades model optimisation for speed — bespoke deep learning or complex NLP requires custom development outside the platform |
| +AutoML platform reduces data science team dependency — business analysts can build and deploy models with minimal ML expertise | -Consulting services are platform-led, not custom — less suitable for unique ML architectures that don't fit the DataRobot paradigm |
| +Platform-native MLOps includes model monitoring, drift detection, and automated retraining out of the box | |
| +Breadth of pre-built accelerators across financial services, healthcare, and manufacturing reduces custom build time |
DataRobot vs alternatives
How DataRobot compares to the other top Machine Learning agencies.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tiger Analytics | Fortune 1000 enterprises needing production-grade ML across CPG,... | The largest pure-play ML and advanced analytics specialist with 5,000+ dedicated practitioners across six countries | 4.8 | Full comparison |
| Forte Group | Mid-market and enterprise teams that need ML treated... | Architecture-first ML delivery with AI embedded at every layer of the software stack, not added as an afterthought | 4.6 | Full comparison |
| Tensorway | Mid-market teams needing senior deep learning expertise in... | Boutique deep learning specialist with direct senior engineer access and AWS Premier Partner status, backed by Anadea's 25-year delivery track record | 4.5 | Full comparison |
| Fractal Analytics | Fortune 500 enterprises in CPG, financial services, or... | Deep Fortune 500 CPG and financial services track record with 5,000+ practitioners and a newly public balance sheet for long-term contracts | 4.4 | Full comparison |
| Quantiphi | Enterprises needing production ML on AWS with strong... | AWS Premier ML Consulting Partner with proprietary NeuralOps framework that accelerates time from training to production deployment | 4.3 | Full comparison |
| Sigmoid | Enterprises in CPG, retail, and BFSI that need... | Sequoia-backed firm combining data engineering and ML under one delivery team — eliminates the handoff friction that slows model deployment | 4.3 | Full comparison |
| DataForest | Growth-stage startups and mid-market teams needing production ML... | Clutch 5.0 / 27 reviews with project minimum from $8K — highest verified quality-to-price ratio at the accessible end of the market | 4.2 | Full comparison |
| InData Labs | E-commerce, healthcare, and fintech teams needing NLP, computer... | Top-10 Clutch-ranked cognitive computing and NLP specialist with competitive rates relative to Western boutiques of comparable review depth | 4.2 | Full comparison |
| RTS Labs | Mid-sized businesses in financial services or healthcare making... | Named top US ML consultant for mid-market businesses in 2026 — focused entry point with accessible minimums and healthcare/fintech domain depth | 4.2 | Full comparison |
| Grid Dynamics | Fortune 1000 enterprises in retail, CPG, or media... | Among the strongest retail and e-commerce AI practices globally, with verifiable ROI metrics from PayPal, eBay, and major US retailers | 4.1 | Full comparison |
| N-iX | Enterprises in manufacturing, industrial IoT, or retail needing... | Named enterprise clients (Bosch, Siemens, eBay) across manufacturing and retail with 2,400+ engineers spanning software, embedded systems, and cloud ML | 4.1 | Full comparison |
| LeewayHertz | E-commerce, logistics, and financial services teams needing AI... | Forbes top-10 AI firm acquired by The Hackett Group — combining engineering delivery with enterprise AI strategic advisory capability | 4.1 | Full comparison |
| LatentView Analytics | Fortune 500 technology, CPG, and financial services firms... | Publicly listed analytics firm with 50+ Fortune 500 clients and deep CPG/tech marketing analytics capability including marketing mix modelling | 4.1 | Full comparison |
| Thoughtworks | Enterprises prioritising ML engineering rigour, responsible AI governance,... | AI-first consultancy with a structured engineering discipline — TDD, continuous deployment, and responsible AI built into ML delivery rather than grafted on afterwards | 4.0 | Full comparison |
| ScienceSoft | Manufacturing, healthcare, and oil & gas enterprises needing... | 35+ years of operation with ISO 9001 and ISO 27001 certifications — provides compliance-mandated vendor stability rare in the ML agency market | 4.0 | Full comparison |
| Oxagile | Media, healthcare, and manufacturing enterprises needing production computer... | 20-year heritage in video technology and media AI translates directly into best-in-class computer vision delivery for media, broadcast, and content platforms | 4.0 | Full comparison |
| Innowise | European enterprises in healthcare, financial services, or logistics... | ISO-certified ML delivery with 1,600+ engineers and GDPR-by-design data processing — strong fit for EU-regulated enterprise buyers | 4.0 | Full comparison |
| Miquido | Product companies in streaming, fintech, or healthtech needing... | Rare combination of ML, product design, and mobile engineering under one studio — ideal for building AI-powered consumer applications without managing multiple vendors | 4.0 | Full comparison |
| Itransition | Large enterprises seeking a stable 25-year vendor with... | Long-established 25-year vendor with 3,000+ engineers providing low-risk ML delivery for enterprises that value breadth and vendor stability over specialisation | 4.0 | Full comparison |
| Algoscale | Growth-stage and mid-market enterprises that need ML and... | Data-engineering-first ML delivery prevents the common failure where ML models are built on unreliable pipelines — end-to-end ownership from raw data to deployed model | 4.0 | Full comparison |
| Acropolium | European mid-market businesses in hospitality, logistics, or healthcare... | Munich-based EU-native ML boutique with specific delivery depth in hospitality, logistics, and healthcare — valuable for German-speaking and EU-regulated enterprises | 3.9 | Full comparison |
| DataArt | Financial services, media, and healthcare enterprises needing ML... | Software-engineering-first culture produces ML systems designed for 5-10 year production lifespans — maintainability and stability over speed-to-market | 3.9 | Full comparison |
| Addepto | Manufacturing, logistics, and retail SMEs needing a focused... | Focused vertical expertise in manufacturing predictive maintenance and retail AI at boutique scale — avoids the generalist overhead of larger firms for targeted use cases | 3.9 | Full comparison |
| BairesDev | US enterprises needing high-volume ML engineering hours with... | Latin American delivery provides full US timezone overlap and real-time collaboration at rates 30–50% below comparable US-onshore ML engineers | 3.9 | Full comparison |
| Intellias | Automotive, financial services, and retail enterprises needing ML... | Strongest automotive ML capability in this review — ADAS, connected vehicle data, and in-car AI built for a segment most ML agencies cannot credibly claim | 3.9 | Full comparison |
| EPAM Systems | Large enterprises needing scale, global delivery coverage, and... | Global scale with 58,000+ engineers and top-3 Glassdoor AI company ranking — rare ML delivery capacity for simultaneous large enterprise programmes | 3.9 | Full comparison |
| Binariks | Healthcare, SaaS, and fintech product teams needing accessible... | Accessible $15K minimum with healthcare and fintech domain ML experience — lower entry cost than larger European peers without sacrificing engineering quality | 3.8 | Full comparison |
| Softeq | Manufacturers, robotics companies, and IoT product builders needing... | Unique full-stack hardware-to-cloud capability — ML embedded into firmware and device systems without requiring a separate hardware engineering partner | 3.8 | Full comparison |
| Ekimetrics | CPG, retail, and media brands needing marketing mix... | Econometric and causal ML focus delivers explainable business-driver insights rather than black-box predictions — strongest for marketing analytics and brand measurement | 3.8 | Full comparison |
| BCG X | C-suite-sponsored AI transformation programmes where strategic consulting and... | BCG strategy consulting credibility combined with 3,000+ engineering practitioners — closes the strategy-to-build gap that typically requires two separate partners | 3.8 | Full comparison |
| Accenture AI | Global Fortune 500 enterprises needing enterprise-wide AI transformation... | 53,000+ dedicated AI practitioners — the only partner that can run simultaneous large-scale ML programmes across multiple continents without staffing constraints | 3.8 | Full comparison |
| Wipro AI | Large enterprises already in Wipro's managed services or... | Enterprise IT governance DNA applied to ML — model versioning, release governance, and audit trails built for highly regulated enterprise environments | 3.7 | Full comparison |
| Deloitte AI | Large enterprises needing AI delivery combined with regulatory... | Only Big Four firm with an AI Studio network and the ability to combine AI technical delivery with tax, audit, and regulatory advisory under one professional services relationship | 3.7 | Full comparison |
| IBM Consulting AI | Large enterprises with IBM infrastructure or WatsonX commitments... | WatsonX enterprise AI platform combined with IBM's 100+ year track record in regulated enterprise environments — strongest for clients already in the IBM ecosystem | 3.6 | Full comparison |
| Iguazio | Enterprises with existing ML models that need production-grade... | MLOps platform specialist with real-time AI serving and multi-cloud/edge deployment — best for operationalising models rather than building them | 3.5 | Full comparison |
DataRobot FAQ
What is DataRobot?
DataRobot was founded in 2012 and is headquartered in Boston, Massachusetts, with 863 employees as of recent figures. It is the category-defining automated machine learning (AutoML) platform vendor with approximately $285M in annual recurring revenue and a $6.3B valuation. DataRobot's consulting and ML development services are platform-led — clients use its enterprise AI cloud to automate model selection, training, evaluation, and deployment — with Quickstart programmes designed to take clients from concept to production in under 90 days. Its value proposition is speed and repeatability: organisations that need ML models deployed quickly without building bespoke data science infrastructure benefit most from DataRobot's platform approach.
How much does DataRobot charge?
DataRobot uses fixed project, retainer pricing. Minimum engagement starts at $50K. A discovery call is required to get project-specific quotes.
What tech stack does DataRobot use?
DataRobot works with AutoML, Python, AWS, Azure, GCP, Kubernetes, Snowflake, Databricks, REST API. Primary industries served include Financial Services, Healthcare, Retail / E-commerce, Manufacturing, Logistics.
Is DataRobot right for enterprise?
Enterprises wanting rapid ML deployment via an enterprise AutoML platform rather than bespoke custom model development. 863 team size. Key consideration: Platform lock-in: migrating away from DataRobot once production models are embedded requires significant re-engineering.
What are the best DataRobot alternatives?
The best alternatives to DataRobot depend on your use case. Top options are:
- Tiger Analytics: the largest pure-play ml and advanced analytics specialist with 5,000+ dedicated practitioners across six countries
- Forte Group: architecture-first ml delivery with ai embedded at every layer of the software stack, not added as an afterthought
- Tensorway: boutique deep learning specialist with direct senior engineer access and aws premier partner status, backed by anadea's 25-year delivery track record
Compare DataRobot with other Machine Learning agencies
DataRobot vs Tiger Analytics DataRobot vs Forte Group DataRobot vs Tensorway DataRobot vs Fractal Analytics DataRobot vs Quantiphi DataRobot vs Sigmoid DataRobot vs DataForest DataRobot vs InData Labs DataRobot vs RTS Labs DataRobot vs Grid Dynamics DataRobot vs N-iX DataRobot vs LeewayHertz DataRobot vs LatentView Analytics DataRobot vs Thoughtworks DataRobot vs ScienceSoft DataRobot vs Oxagile DataRobot vs Innowise DataRobot vs Miquido DataRobot vs Itransition DataRobot vs Algoscale DataRobot vs Acropolium DataRobot vs DataArt DataRobot vs Addepto DataRobot vs BairesDev DataRobot vs Intellias DataRobot vs EPAM Systems DataRobot vs Binariks DataRobot vs Softeq DataRobot vs Ekimetrics DataRobot vs BCG X DataRobot vs Accenture AI DataRobot vs Wipro AI DataRobot vs Deloitte AI DataRobot vs IBM Consulting AI DataRobot vs Iguazio
Last reviewed: July 2026. Verify all details directly with DataRobot before making a decision.