JADBio
JADBio: A focused AutoML workspace for scientific teams that need explainable models. Ranked #18 of 29 in AutoML Software by our editors (7.5/10); pricing: Free plan · 14-day trial; best for scientific teams needing interpretable AutoML.
At a glance
- Editor score7.5 / 10
- PricingFree plan · 14-day trial
- Best forScientific teams needing interpretable AutoML
- Free planYes
- Paid from$2,199/mo
- Feature engineeringYes
- Founded2019 · Heraklion, Crete, Greece; Los Angeles, California, US
- Facts checked21 Sep 2026
Where it wins
- Automates feature, algorithm, and hyperparameter selection
- Supports classification, regression, and survival analysis
- Offers explainability, offline export, REST API, and Python access
Where it doesn't
- The paid Team plan is $2,199 per team per month annually
- Advanced paid tiers use contact-sales pricing
- Business Pro is needed for private repositories and on-premise delivery
Our verdict on JADBio
JADBio is a no-code automated machine learning platform for biomedical and multi-omics work. It is aimed at life-science professionals, scientific teams, and data analysts who need to upload and wrangle data, identify predictive features, compare modeling configurations, and create classification, regression, or survival models. Its focus on feature interpretation and interpretable-model visualization makes it suitable when model reasoning matters alongside predictive modeling.
The free Basic plan includes data uploading and wrangling, single feature selection, basic tuning, feature interpretation, model visualizations, and one model export. It also includes a 14-day Team trial. The paid Team plan is listed at $2,199 per team per month with annual billing and adds full functionality, multiple feature selection, extensive tuning, API access, batch analysis, and a premium support SLA. Other paid options include capabilities such as survival analysis, unlimited model export, public repository connections, enterprise-grade workflows and controls, AWS container or on-premise delivery, advanced analysis for images, signals, and single-cell data, user-defined code and algorithms, private repository connections, and a platinum support SLA.
JADBio fits workflows that combine a web interface with API access and offline prediction. Its REST API and Python client support programmatic use, while batch analysis and model export extend models beyond the main interface. Public and private repository connections support repository-based workflows, with private connections and on-premise delivery reserved for higher-tier capabilities. Teams should choose JADBio when automated selection, scientific data workflows, and explainability are central requirements. It is less suited to organizations seeking broad value at a lower paid price, or teams that need advanced deployment and repository controls without moving to higher-priced plans.
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JADBio pricing
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JADBio fact sheet
| Free plan | Yes |
|---|---|
| Paid from | $2,199/mo |
| Feature engineering | Yes |
| Automated model selection | Yes |
| Model explainability | Yes |
| Deployment options | Batch |
| Workflow interface | Both |
| Hosting model | Both |
| Free trial | 14 days · no card needed |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Compliance & security | GDPR |
| Support | Email, Phone |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 2 integrations: Public repositories, Private repositories |
| Pricing | Free plan · 14-day trial (source) |
| Website | jadbio.com |
| Facts checked | 21 Sep 2026 |
JADBio integrations
JADBio lists 2 integrations on its own site.
- Public repositories
- Private repositories
Alternatives to JADBio
- SAS ViyaA broad, governed AutoML platform for complex enterprise and regulated workloads.9.3
- DataRobotA focused enterprise AutoML platform with forecasting, deployment, monitoring, and governance.9.1
- IBM Watson StudioA broad AutoML workspace for teams that need collaboration, deployment and governance.9.0
Also Ranked In
JADBio is ranked in 2 of our directories.
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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