Stella is the clinical reasoning co-pilot built for medical students — with a 3-tier memory architecture that remembers your patient cases, tracks your weak topics across sessions, and never throttles you mid-differential.
↑ The actual product. Your name, your streak, your last session — right where you left it.
You're not studying wrong.
You're studying with tools built for someone else.
Generic chatbots were designed for emails and essays. When you bring them a 2am clinical vignette with three distractors and a side of pathophysiology, they give you a paragraph and a shrug.
You re-explain your patient case from scratch every session. The chatbot has no idea you already covered the RTA Type 1 mechanism three messages ago.
Commercial caps shut you down at the worst moment — right when you're 12 sessions deep and finally cracking a high-yield case.
You don't just need the right answer. You need to understand why the A is right, why B is a trap, and how to walk that logic in an oral exam.
Stella behaves like a senior resident sitting next to you. Three layers of memory, four response modes, four exam-specific personas, and a Compaction Engine that turns every session into the foundation for the next one.
Stella's L1 / L2 / L3 architecture scope-partitions your knowledge state — so your next session begins exactly where the last one ended.
The immediate buffer. Holds the active patient history, the labs you just pasted, the mechanism you're tracing, the distractors you're ruling out. Evolves in real time as you think out loud.
Stella parses every exchange to classify each topic as Weak, Needs Work, Strong, or Neutral. Routes your next review, your next MCQ, your next flashcard to where it matters most.
At session end, the Compaction Engine distills everything you covered into a chronological ledger. Next time you open Stella, she loads your L3 — and you're back in context within seconds.
Every concept you touch becomes a node. Every weak topic gets a recovery route. Every session adds a layer. Over time, Stella's memory becomes indistinguishable from a study partner who's been with you since day one.
When a study session ends, an async Compaction Engine distills the core findings, the diagnostic pitfalls, and the mechanism threads into a permanent entry in your L3 ledger. You never re-cover ground.
Drop any unstructured lab panel into Stella — CBC, LFT, ABG, electrolytes, renal profile, all of it. She identifies abnormals, detects patterns like metabolic acidosis with respiratory compensation, ranks differentials, and gives you exam-ready viva pearls.
Type /test and Stella generates a 10-question widescreen MCQ block from exactly what you just studied. Every wrong answer triggers a mechanism breakdown — and queues the concept straight into your L2 weak topic tracker for re-test.
Highlight anything in chat and turn it into a card. Every card supports both flip mode (active text recall) and MCQ mode (quiz-style testing) — switch mid-review with a single tap. Failing a card queues a mechanism-first study note generated by Stella.
Some moments call for mechanism. Some call for speed. Some call for a USMLE-style throwdown. Switch modes mid-session — Stella keeps the L1 / L2 / L3 context intact while changing how she answers.
Full depth. Headers, mechanisms, traps, pearls. The mode you default to when you actually want to learn something.
Stella picks the shape — paragraph, list, table — based on what fits the question. Best for browsing ideas.
1-6 lines per question. Reasoning off. Pure recall mode for when you're cramming a deck before rounds.
Scenario → A-E. Explanation revealed only after you commit. The exam simulator.
Pick the curriculum. Pick the response mode. Stella routes the entire session through the right clinical engine — no manual configuration, no prompt engineering.
First Aid–aligned. NBME-style vignettes. Mechanism-first explanations. Dedicated biostatistics and ethics routing.
Subject-specific modules for anatomy, physiology, biochemistry, pathology, pharmacology, and forensic medicine.
Switch seamlessly between USMLE and MBBS framing. For residency-bound students preparing for both ecosystems.
Lower cognitive load. More Socratic. Built for late nights when you can't stare at another wall of text.
The Daily Planner doesn't ask what you want to study — it asks what you should study, based on your L2 weak topics, your last 5 L3 digests, and your manual focus. Outputs an Apple-grade schedule with priority topics, review blocks, MCQ practice, and end-of-day checkpoints.
No single model wins every workload. Stella's routing matrix picks the right engine per query — private local, premium clinical, or high-availability cloud failover.
Run private, offline, high-speed clinical models directly on your consumer RTX hardware. Your data never leaves your machine. Ideal for sensitive patient data and uninterrupted deep work.
Premium clinical reasoning engine optimized for deep pathophysiological analysis, distractor breakdown, and differential ranking. Used for vignettes, lab mode, and mechanism explanations.
High-speed cloud fail-safe that ensures constant access to study materials even when local servers are offline. Auto-engages when the primary engine is throttled or unavailable.
"I haven't re-explained a patient case in three weeks. My UWorld recall rate went from 60% to 84%."
"It's the first AI I've used that actually remembers my weak topics across sessions. The Compaction Engine is magic."
"Stella's Lab Mode saved me on a real patient last week. I saw the same pattern in 30 seconds. That's not a chatbot, that's a colleague."
All plans unlock the 3-tier memory, lab mode, daily planner, flashcards, and the full clinical routing engine. Usage splits into Weekly Usage + a Flex Reserve for bursts — no hard 5-hourly or weekly caps, ever.
Stella is in active beta — a closed cohort of medical students stress-testing the memory architecture and clinical engines. New slots open every Monday. No card to start.
Built for USMLE & MBBS · 4.9★ avg · 89% retention