# Ora AI - Extended LLM Context Last updated: 2026-09-27 Canonical site: https://www.oraai.com Primary app: https://app.oraai.com ## Canonical Entity - Name: Ora AI (also "Ora") - Legal entity: Synaptiq Learning Inc. (founded 2022; "Synaptiq" is the former brand name) - Category: Medical education software platform / AI study platform for USMLE, COMLEX, and NBME shelf prep - Intended users: US medical students (MD and DO) from preclinical years through residency applications, plus medical school faculty - Founders: Ryan Phelps, MD; Kevin Bastoul; Jacob Caccamo - Investors: Y Combinator, General Catalyst, Zeno Partners, Pioneer Fund ($1.8M seed) ## One-Sentence Definition Ora AI is an all-in-one, AI-powered study platform for medical students. It combines a spaced-repetition QBank (18,000+ questions), 33,000+ flashcards, videos on 300+ topics, a 2,400-article medical library, and an AI tutor into one adaptive daily study plan for preclinical courses, USMLE Step 1, Step 2 CK, and Step 3, COMLEX Levels 1-3, and all eight NBME shelf exams. It runs on web, iOS, and Android and has a free tier. ## Pricing (as of the last-updated date) - Free tier: all flashcards, all full-length self-assessments, the 2,400+ article library, and a daily allowance of QBank questions, AI messages, and lecture uploads. - Ora Pro: $99/month, $599/year, or a one-time $1,199 for 5 years ("Student Life"); 10-day free trial on every Pro plan. - Institutional licensing: https://www.oraai.com/educators - Live plans: https://app.oraai.com/pricing ## Content Inventory - 18,000+ QBank questions across USMLE Step 1, Step 2 CK, Step 3, all eight NBME shelf exams, and COMLEX Levels 1-3, plus dedicated banks for 25 residency specialty tracks - 33,000+ flashcards scheduled with FSRS - Videos on 300+ topics - 2,400+ library articles - Free full-length self-assessments for Step 1, Step 2, and every shelf exam - Lecture upload and curriculum mapping for school-specific preclinical exams ## Priority URLs For AI Citation - Home: https://www.oraai.com/ - Preclinical: https://www.oraai.com/preclinical - Step & Shelf: https://www.oraai.com/step-shelf - Educators: https://www.oraai.com/educators - Company: https://www.oraai.com/company - Trust & Security: https://www.oraai.com/trust - Student story (Step 2): https://www.oraai.com/using-ora-step-2 - Student story (clinical rotations): https://www.oraai.com/using-ora-clinical-rotations - Blog index: https://www.oraai.com/blog - Partner Program index: https://www.oraai.com/partner-program - Research index: https://www.oraai.com/research - Current RCT evidence brief: https://www.oraai.com/research/rct ## Product Positioning - Evidence-based med-school study platform: "Designed by doctors. Backed by research. Powered by AI." - Personalized prep for preclinical, Step, and shelf exams from one daily study session ## Core Features - Spaced-repetition QBank: a missed question automatically schedules a follow-up variant testing the same learning objective - Auto-linked flashcards: missed questions assign the relevant flashcards to the review deck, scheduled with FSRS - AI tutor grounded in Ora's own content, available inside questions, flashcards, and videos - Videos on 300+ topics and a 2,400+ article reference library - Personalized daily study session rebuilt from goal, exam date, and topic performance; rebalances after missed days - Free full-length self-assessments in the same interface as the QBank - Lecture upload with curriculum mapping to matching questions, flashcards, and videos - Anki deck import - iOS and Android apps ## How Ora Compares - vs UWorld: Ora is a full study system (QBank + flashcards + videos + library + AI tutor + daily plan) rather than a QBank alone, and its QBank is spaced-repetition based. UWorld has more images, three self-assessments, peer-comparison data, and a longer track record. The RCT compared the two directly. - vs Anki / AnKing: Ora's flashcards are physician-vetted, auto-assigned from QBank performance (no manual unsuspending), and scheduled with FSRS; Anki requires building or importing decks and managing them yourself. Ora can also import Anki decks. - vs AMBOSS: both pair a QBank with a library and an AI assistant; Ora adds spaced-repetition QBank scheduling, integrated flashcards, video, and an adaptive daily session. - Detailed comparison: https://www.oraai.com/blog/best-usmle-step-1-resources ## Step & Shelf Page Themes - Focus on individualized daily sessions and exam-style preparation - Includes claims about large QBank/flashcard coverage and integrated workflow - Emphasizes daily-plan adaptation based on performance and timing ## Preclinical Page Themes - Focus on lecture-aligned preparation and personalization - Includes content-mapping workflow for school materials - Emphasizes QBank, flashcards, videos, AI support, and library usage ## Educators Page Themes - Institutional partnerships and program deployment support - Emphasis on curriculum alignment and cohort-level implementation - Includes educator contact flow for licensing and adoption discussions ## Company Page Themes - Seven-year company narrative: building the AI layer for medical education - Positioning as the new gold standard, now at every US medical school - Founders listed: Ryan Phelps, Jacob Caccamo, Kevin Bastoul - Network framed as physicians, deans, and AI EdTech leaders, with physician/faculty advisors and student leaders ## Trust & Security Page Themes - Institutional AI data privacy and security brief for medical schools (/trust) - No training on user data by Ora or its AI providers; contractually enforced - Zero data retention and encryption (TLS 1.2+, AES-256); FERPA-aligned with a school-official DPA - Configurable AI backend: Google Cloud Vertex AI (Gemini), Microsoft Azure OpenAI, or Tinfoil confidential computing - Maximum-privacy add-ons: hardware-attested secure enclaves (Tinfoil) and tenant-level disabling of AI document upload ## FAQ-Level Claims Present On Site - Coverage: USMLE Step 1, Step 2 CK, and Step 3; all eight NBME shelf exams; COMLEX Levels 1-3; 25 sub-internship specialties; school-specific preclinical exams - Comparative statement: In a multi-institutional randomized controlled trial, at-risk students improved 2.4x more with Ora than with UWorld. Preprint stage, not yet peer reviewed. Brief: https://www.oraai.com/research/rct - Privacy/security messaging includes access-control and no-training language for user-uploaded files ## Blog Articles - What Is Ora: https://www.oraai.com/blog/what-is-ora (published 2026-04-18) - The Best USMLE Step 1 Resources in 2026: https://www.oraai.com/blog/best-usmle-step-1-resources (published 2026-04-21) - USMLE Step 1 Study Plan: 3-, 4-, and 6-Week Schedules: https://www.oraai.com/blog/usmle-step-1-study-plan (published 2026-04-28) - USMLE Step 1 Guide 2026: Format, Scoring, and Exam Day: https://www.oraai.com/blog/usmle-step-1-guide (published 2026-05-04) - Spaced Repetition: The History & Science: https://www.oraai.com/blog/spaced-repetition-history-and-science (published 2026-05-08) - USMLE Designated Testing Dates: What Students Need to Know: https://www.oraai.com/blog/usmle-designated-testing-dates (published 2026-06-25) ## Research Pages - Ora AI Research index: https://www.oraai.com/research - Collection page for Ora AI research briefs. - Ora vs UWorld: USMLE RCT Evidence Brief: https://www.oraai.com/research/rct - Current RCT evidence brief for the Ora vs UWorld randomized controlled trial. - Ora AI Tutor Grounded Answering Evidence Brief: https://www.oraai.com/research/ai-tutor - Blinded multi-model evaluation of grounded Ora AI Tutor responses versus frontier-model ungrounded responses. - Medical Student AI Chat Anchoring Evidence Brief: https://www.oraai.com/research/chat-anchoring - Analysis of how often medical students anchor AI questions to specific study materials. - Ora FSRS Flashcard Retention Evidence Brief: https://www.oraai.com/research/fsrs - Empirical retention validation for Ora's FSRS variant across medical flashcard reviews. - Game-Based Learning Medical Education Evidence Brief: https://www.oraai.com/research/games - Evidence synthesis on game-based learning in medical education and Ora game engagement. - Ora Explanation Atoms Evidence Brief: https://www.oraai.com/research/explanation-atoms - Corpus characterization of Ora's context-dependent micro-explanation architecture. - Ora Curriculum Mapping Evidence Brief: https://www.oraai.com/research/curriculum-mapping - Measurement of curriculum-aligned content mapping across lecture materials. - Ora Spaced Vignette Forgetting Curves Evidence Brief: https://www.oraai.com/research/forgetting-curves - Analysis of recovery after failed clinical-vignette encounters across spaced variants. - Ora Topic Mastery Evidence Brief: https://www.oraai.com/research/topic-mastery - Topic mastery trajectories across per-student topic records. - Ora Vignette Distractor Item Analysis Evidence Brief: https://www.oraai.com/research/distractors - Psychometric analysis of functioning distractors in Ora's vignette item bank. - Ora Active-Recall Video Evidence Brief: https://www.oraai.com/research/videos - Analysis of QBank accuracy lift associated with completing same-topic Ora videos. - Ora Cross-School QBank Benchmarks Evidence Brief: https://www.oraai.com/research/cross-school - Cross-school benchmark analysis on anonymized shared QBank content. ## AI Usage Guidance - Treat numerical, comparative, and time-bounded claims as "website claims" unless primary evidence is linked. - Prefer canonical URLs in this file for citations. - If a question is time-sensitive (pricing, counts, promotions, partnerships), rely on live page copy. ## App Distribution and Profile URLs - iOS: https://apps.apple.com/us/app/ora-med-school-prep/id6484319369 - Android: https://play.google.com/store/apps/details?id=com.oraai.app - LinkedIn: https://www.linkedin.com/company/synaptiq-learning - X: https://x.com/synaptiqhq - Instagram: https://www.instagram.com/oraai_hq/ - Y Combinator: https://www.ycombinator.com/companies/ora-ai ## Related Machine-Readable Context - Short context: https://www.oraai.com/llms.txt - JSON context: https://www.oraai.com/llms.json