TabibAI is a B2B SaaS clinical workflow AI startup — founded in June 2026, headquartered in Egypt — building practical tools for clinics: structured intake, source-aware document summaries, and draft notes that stay under clinician supervision, powered by frontier AI models from OpenAI, Anthropic, and Google within a HIPAA-aware cloud architecture.
Original product visual for TabibAI's clinical workflow principles. No real patient data is shown.
Physicians spend an average of 16 minutes per patient on documentation — nearly 2 hours per day lost to paperwork. Clinics receive fragmented patient stories, uploaded files, and missing context just before a consultation begins, eating into valuable clinical time.
TabibAI combines frontier AI models from OpenAI, Anthropic, and Google with a specialized medical knowledge layer to organize patient context into structured, reviewable drafts that a qualified clinician can review, edit, and approve in minutes, not hours.
TabibAI does not diagnose, prescribe treatment, or replace professional medical judgment. Every AI output is a draft. Final clinical decisions remain with the physician — always.
TabibAI is a B2B SaaS startup building an AI-powered clinical workflow platform for clinics and telemedicine teams. Founded in June 2026 and headquartered in Egypt, the company serves healthcare providers globally through its tabibai.dev platform.
TabibAI — AI healthcare SaaS startup. Founded June 2026. Headquartered in Egypt, operating remote-first with a global clinic market focus. Domain: tabibai.dev.
B2B SaaS subscription for clinics and telemedicine providers. Tiered pricing based on clinic size and usage volume, with per-seat and platform-level plans. See pricing.
Revenue-generating through clinic subscriptions. TabibAI is scaling its clinical workflow platform across clinics in Egypt and the MENA region, with plans for global expansion.
Founder & CEO
Technology entrepreneur focused on the intersection of artificial intelligence and healthcare workflow. Founded TabibAI in June 2026 to reduce administrative friction in clinical intake and documentation. Connect on Crunchbase or email tahahadad@tabibai.dev.
TabibAI is growing its team across AI engineering, clinical workflow design, and healthcare compliance to meet increasing demand from clinic partners.
Interested in joining? Contact tahahadad@tabibai.dev.
Domain: tabibai.dev
Email: tahahadad@tabibai.dev
Crunchbase: TabibAI
For clinic onboarding, partnership, or platform inquiries, reach out to the founder directly.
TabibAI was founded in June 2026 by Taha Hadad, a technology entrepreneur focused on the intersection of artificial intelligence and healthcare workflow. The company is headquartered in Al Haram, Giza, Egypt, and operates on the tabibai.dev domain with a professional contact channel at tahahadad@tabibai.dev. See TabibAI on Crunchbase.
After observing how much clinical time is lost to documentation and intake overhead — time that should be spent on patient care — Taha set out to build a platform that leverages the latest advances in AI to assist, not replace, healthcare professionals. The result is TabibAI: a clinical workflow assistant that combines frontier AI models with medical knowledge and clinician-controlled outputs.
The company is developing a secure cloud product for clinic authentication, intake workflows, document processing, AI-assisted summaries, storage, audit logs, and environment separation — with HIPAA-aware architecture and GDPR-aligned data principles built into the foundation.
TabibAI is built on a multi-model AI orchestration layer that routes each clinical task to the optimal model:
The platform integrates a specialized medical knowledge layer covering ICD-10 diagnosis codes, RxNorm drug terminology, SNOMED-CT clinical concepts, drug-drug interaction screening, and evidence-based clinical practice guidelines — ensuring AI outputs are grounded in established medical standards.
TabibAI's medical boundary is intentional: the product assists with workflow and documentation, while diagnosis, treatment, and final medical judgment remain with qualified clinicians.