EazyML
EazyML is a privately held, bootstrapped US software company that sells a transparent machine learning platform with explainable AI, augmented intelligence, text analytics, and rule automation, targeting financial services, healthcare, manufacturing, and other regulated enterprises via freemium self-serve plus Pro/Platinum enterprise contracts.
- Company typePrivate
- Founded2018
- HeadquartersFreehold, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
What EazyML does
EazyML (operated under the legal entity Datanomers) is a US-based software company that sells a Transparent Machine Learning platform designed to make predictive models explainable to non-technical business users and compliant with regulated-industry audit requirements. Founded in 2018 by Deepak Dube, Ph.D., and headquartered in Freehold, New Jersey, the company has built a modular SaaS product spanning Explainable AI (rule-and-threshold predictions with confidence scores), Augmented Intelligence (automatic business-insight mining with predictor thresholds), Data Quality Assessment, Text Analytics/NLP (sentiment, topic modeling, concept extraction, GloVe embeddings), an automated Rule Builder (claimed to cut rule-update cycles from three months to three days), and a Generative AI module for document processing. The platform exposes a no-code Q&A GUI for business users and a REST/Python API for developers, and integrates with AWS, Azure, and Google data sources.
The company monetizes through a freemium-to-enterprise tiered subscription: Free Trial, Standard ($19/month), Deluxe ($39/month), and Premium ($79/month) for self-serve users, plus Pro and Platinum enterprise tiers with custom pricing, multi-year contracts, and bundled professional services billed by seniority. Go-to-market is hybrid — product-led growth via self-signup at app.eazyml.com, supplemented by direct field sales for Pro/Platinum deals and PoC engagements. EazyML serves financial services, pharma/healthcare, manufacturing, insurance, retail, telecom, contact centers, and education, with named logos including Oracle Financial Services, Amcor, Alliant Credit Union, Amount, Regeneron, and Southern Utah University. The company is privately held and bootstrapped (no external funding rounds disclosed in the data), with 11–50 employees and active marketing channels spanning content, webinars, university workshops, and Forbes thought leadership by the CEO.
EazyML firmographics
Firmographics- Name
- EazyML
- Legal name
- Datanomers
- Website
- https://eazyml.com
- Company type
- Private
- Founded year
- 2018
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Short description
- EazyML is a privately held, bootstrapped US software company that sells a transparent machine learning platform with explainable AI, augmented intelligence, text analytics, and rule automation, targeting financial services, healthcare, manufacturing, and other regulated enterprises via freemium self-serve plus Pro/Platinum enterprise contracts.
- Ownership category
- akta.pro rank
EazyML industry classification
Industry- Product category
- Machine Learning Platform
- NAICS
- Software Publishers (5132), Custom Computer Programming Services (541511), Other Computer Related Services (541519)
- SIC
- Services-Prepackaged Software (7372), Services-Computer Programming Services (7371), Services-Computer Programming, Data Processing, Etc. (7370)
- akta.pro primary industry
- AutoML & Low-Code ML Platform Operations (HDAAABAL)
- akta.pro secondary industries
- Model Testing, Validation & Quality Assurance (HDAAABAH), Privacy-Preserving ML & Data Protection (e.g., federated learning, differential privacy) (HDAAAMAD)
Keywords
Where EazyML is headquartered
LocationHeadquarters
- HQ city
- Freehold
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
EazyML business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Technology or R&D, Personnel, Marketing or Sales, Infrastructure, Operations
Revenue model
- SaaS Subscription - Tiered Plans: EazyML offers tiered subscription plans (Free Trial, Standard $19/mo, Deluxe $39/mo, Premium $79/mo) with increasing dataset limits, training/test datasets, and file size allowances. Higher tiers include email/phone support.
- Enterprise/Custom Pricing - Pro & Platinum: Custom pricing for Pro (unlimited datasets, 8 hours training, optional professional services add-ons, one-time setup fee) and Platinum tiers (everything in Pro plus senior professional & advisory services, priority support). PoC pricing depends on customer requirements with EazyML team developing use cases.
- Professional Services: Professional services included in Pro and Platinum tiers for developing use cases and delivering business objectives. Billed according to seniority of resource and number of hours contracted.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Monthly | Free trial tier with basic capabilities for evaluation |
| Subscription | Monthly | Entry-level paid tier for individual users |
| Subscription | Monthly | Mid-tier plan with expanded capabilities |
| Subscription | Monthly | High-end individual/small team tier |
| Subscription | Multi-year contract | Enterprise tier with custom pricing |
| Subscription | Multi-year contract | Top-tier enterprise with full service |
Go-to-market motion1 record
Distribution channels3 records
Marketing channels8 records
EazyML product offering
Product offeringCore offering
EazyML sells a Transparent Machine Learning SaaS platform that builds predictive models from structured and unstructured data and explains every prediction as a simple rule with a confidence score. The product is offered as a self-serve web application with tiered subscription plans and as enterprise Pro/Platinum deployments with bundled professional and advisory services, targeting regulated industries that require auditability and human-machine trust.
Product overview
EazyML is a Transparent Machine Learning platform offering a unified core platform with modular add-on capabilities. The core EazyML Platform processes structured data and unstructured text to build predictive models with full explainability. Key modules include: Explainable AI (explains predictions as rule-based reasons with confidence scores), Augmented Intelligence (automatically mines business insights), Data Quality (assesses data fitness before modeling), Text Analytics/NLP (processes unstructured text for enhanced predictions), Rule Builder (automated rule updates via simple English), and Generative AI (document processing). The platform supports no-code GUI access for business users and Python/REST APIs for developers, scales horizontally and vertically in cloud environments, and is designed for regulated industries requiring audit trails and regulatory compliance.
Differentiator
Problem solved
Functional benefit
Products and services
- EazyML Platform Transparent machine learning platform that builds predictive models from structured and unstructured data, explaining every prediction as a simple rule with influential predictors, thresholds, and a confidence score. Sold as a self-serve web application with tiered subscriptions (Free Trial, Standard $19/mo, Deluxe $39/mo, Premium $79/mo) and as enterprise Pro/Platinum deployments with bundled professional and advisory services for regulated industries.
- Augmented Intelligence Capability that mines data automatically to extract insights about business dynamics, assigning thresholds to each predictor and displaying explanations in a human-comprehensible rules-and-thresholds format with actionable confidence scores, available via the platform GUI and APIs.
Quantifiable outcome
- Rule updates reduced from 3 months to 3 days using Rule Builder
- +1 more outcomes
Companies that use EazyML
Customer profileNamed customers7 records
Segments8 records
Ideal customer profiles5 records
EazyML technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration4 records
AI capability9 records
Feature7 records
EazyML partnerships and signals
Strategic signalPartnerships
Four partnerships are on record, tiered minor.
- PMSA (Pharmaceutical Management Science Association)minorEazyML co-presented with Regeneron at the PMSA Annual Conference on the topic of Leveraging AI for Strategic Market Protection: A Predictive-Prescriptive Framework.
- Duke UniversityminorEazyML conducted an educational workshop for Duke University students, providing hands-on experience with the ML platform for academic learning purposes.
- Princeton UniversityminorEazyML conducted a workshop at Princeton University to help students learn ML through practical platform usage.
- Southern Utah UniversityminorProf. Courtney Paulson, Director of Business Analytics at SUU, serves as a judge for EazyML hackathons and provided testimonial about the platform being 'truly the next generation ML Platform.'
Scale indicators3 records
Recent moves6 records
Expansion highlights6 records
EazyML competitors and assessment
Company assessmentDirect peers
- Dataiku: Dataiku offers an Everyday AI platform combining visual no-code ML with advanced coding environments. It competes directly with EazyML on democratized ML for business analysts and enterprise governance.
- BigML: BigML provides a consumable, programmable, and scalable Machine Learning platform with explainability. It is comparable to EazyML as a packaged AutoML service aimed at non-technical and technical users.
- DataRobot: DataRobot is an enterprise AutoML platform that builds, deploys, and monitors predictive models. It directly competes with EazyML in automated machine learning for business users, with overlapping capabilities in explainability and governance.
- H2O.ai: H2O.ai provides an open-core ML and AI platform with AutoML, Driverless AI, and explainability features. It is a direct competitor to EazyML in the no-code and explainable ML space for enterprise.
- RapidMiner: RapidMiner (Altair) is a data science platform with AutoML, model interpretability, and visual workflows. It overlaps with EazyML on no-code ML and transparency for enterprise customers.
Broad incumbents
- Amazon SageMaker: Amazon SageMaker is a fully managed ML platform offering AutoML, MLOps, and explainability (SageMaker Clarify). It is a broad incumbent that competes with EazyML on enterprise ML, though it sits within a much larger AWS ecosystem.
- Google Vertex AI: Google Vertex AI provides AutoML, custom training, and explainable AI capabilities within Google Cloud. It is a broad incumbent that competes with EazyML on transparency and enterprise ML services.
- Palantir Foundry: Palantir Foundry is an enterprise data and analytics platform that includes ML and explainable decisioning. It is a broad incumbent serving large enterprises with overlapping transparency and AI governance needs.
- Microsoft Azure Machine Learning: Azure ML offers responsible AI, AutoML, and MLOps within the Microsoft cloud ecosystem. It competes with EazyML on enterprise ML governance and explainability.
Emerging players
- Domino Data Lab: Domino provides an enterprise MLOps platform for managing model development, deployment, and governance. It overlaps with EazyML on enterprise ML lifecycle and explainability, particularly for regulated industries.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks5 records
Key highlights6 records
Customer concentration
EazyML social profiles
Digital presenceEazyML financial estimates
Financial estimateRevenue estimate
Valuation estimate
EazyML leadership team
Management profileNumber of profiles
Profiles7 records
EazyML funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
EazyML M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about EazyML
What does EazyML do?
EazyML sells a Transparent Machine Learning SaaS platform that builds predictive models from structured and unstructured data and explains every prediction as a simple rule with a confidence score. The product is offered as a self-serve web application with tiered subscription plans and as enterprise Pro/Platinum deployments with bundled professional and advisory services, targeting regulated industries that require auditability and human-machine trust.
Is EazyML a public or private company?
EazyML is a private company. It is classified as founder individual operated bootstrapped and is currently operating.
When was EazyML founded?
EazyML was founded in 2018. It employs 11 to 50 people.
Where is EazyML based?
EazyML is headquartered in Freehold, United States, in the North America region.
How does EazyML make money?
Three revenue lines are on record. SaaS Subscription - Tiered Plans are the primary driver. The others are enterprise/Custom Pricing - Pro & Platinum and professional Services.
Who are EazyML's main competitors?
Direct peers on record are Dataiku, BigML, DataRobot, H2O.ai and RapidMiner. Broad incumbents are Amazon SageMaker, Google Vertex AI, Palantir Foundry and Microsoft Azure Machine Learning. Domino Data Lab is listed as an emerging player.
Does EazyML have an API?
Yes. EazyML provides REST APIs for machine learning workflows including data upload/loading, preprocessing (variable data type determination, outlier removal, imputation), model initialization and building, prediction, and explainable AI. APIs use HTTP POST requests with JSON payloads and responses over HTTPS. Available in three environments: Sandbox (restricted, sample datasets only), Development (Trial users), and Production (Standard/Deluxe/Premium subscribers). Authentication via ez_auth endpoint using username/password. Documentation URL: http://eazyml.com/docs. Python client available on GitHub at https://github.com/EazyML/eazyml-client. Developer documentation is at eazyml.com/docs.
What industry is EazyML in?
EazyML's product category is Machine Learning Platform. Its primary akta.pro industry code is HDAAABAL, AutoML & Low-Code ML Platform Operations, with a secondary code of HDAAABAH, Model Testing, Validation & Quality Assurance. Its NAICS code is 5132 and its SIC code is 7372.