Pricing is structured for clinics and telemedicine teams reviewing TabibAI's AI-powered intake, document-review, and physician-reviewed documentation workflow — built on frontier models from OpenAI, Anthropic, and Google and open-weight models including Llama, DeepSeek, and Qwen. Start free, scale as you prove value.
For reviewing the product flow, workspace experience, and fit for your clinic before a paid plan. Full access to all 6 modules with clinical workflow examples.
For small clinics testing intake, document summaries, and physician-ready notes. ROI typically visible within the first 2 weeks.
For telemedicine teams that need custom workflows, environments, and security planning. Scales to 50+ clinicians with enterprise-grade infrastructure.
A clear pricing structure for clinics, with paid plans handled through service agreements and invoices.
| Capability | Product review | Clinic plan | Enterprise plan |
|---|---|---|---|
| Product pages + workspace | Included | Included | Included |
| Sign in with Google (OAuth 2.0) or email + password | Backend verified | Backend verified | Custom auth planning |
| Clinical intake templates | Demo workflows | Clinic-specific | Custom workflows |
| Document processing | Sample summaries | 4+ document types | Cloud architecture scoped |
| AI model access (OpenAI GPT models, Anthropic Claude models, Google Gemini models) | Demo inferences | Full multi-model routing | Custom model configuration |
| Medical knowledge layer (ICD-10, RxNorm, SNOMED-CT) | Reference display | Integrated | Custom integration |
| Staff seats | 1 evaluator | Up to 5 | 50+ with RBAC |
| Audit logging | Basic view | Timestamped actions | Full compliance logging |
| Deployment environment | Shared evaluation | Dedicated production environment | Custom cloud (GCP/AWS/Azure) |
| Commercial terms | Free trial | Monthly subscription | Custom agreement |
Medical note: TabibAI is a workflow and documentation assistant. It does not diagnose, prescribe treatment, or replace professional medical judgment.
Straightforward answers for clinics evaluating a controlled healthcare AI workflow.
Yes. Clinics can review the product workflow using clinical workflow examples before sharing requirements or starting a paid plan. Real patient information should only be used after a proper service agreement and data-handling setup are in place.
Billing starts only after the clinic deployment scope is agreed, including seats, workflow requirements, security expectations, and deployment responsibilities.
Yes. Intake templates, document workflows, seats, and deployment requirements can be adjusted during deployment planning before live clinical use.
Not by default. Export and integration needs vary by clinic and should be scoped explicitly rather than promised as a generic feature.