Delemma is an AI agent for nutrition. It turns your food, biometrics and goals into the next decision — automatically. No labels to read. No spreadsheets to keep.
Delemma began as one person debugging his own metabolism. The principles that worked turned out to be the principles that work for everyone.
In 2023, mid-thesis, jet-lagged, and chronically underslept, I was diagnosed with a runaway A1C of 14%. The clinic's plan was lifelong insulin.
I went home and started treating my body like a system to debug. Every meal logged. Every biometric tracked. Every recommendation cross-checked against the literature.
Sixteen months later A1C was 5.5% — back inside the normal range. The thing that worked wasn't a diet. It was a feedback loop: data in, decision out, signal back.
Pick the goal that fits today's life. Delemma rewires food, biometrics and recommendations around it — and adapts as the goal changes.
Stable life, modern diet — but tired, foggy, sleeping poorly. Delemma maps 49 nutrients against your real intake and surfaces the silent gaps: vitamin D, magnesium, omega-3, B-complex.
Calorie deficits collapse without protein, magnesium, B-complex. Delemma separates "calorie gap" from "nutrient gap" so you keep your metabolism — not just your scale number.
16:8, 18:6, OMAD — the upside lives in the eating window. Delemma calculates exactly the protein, potassium, magnesium and sodium your window needs, and pre-stages electrolyte protocols.
Flux is the conversational core of Delemma. Every reply pulls live signal — biometrics, intake history, energy balance, your goal — and answers in the moment, not in the abstract.
Two models, both ours: one reads the plate, one reads you. Both are trained, shipped and running in the Delemma app today — neither is a wrapper around somebody else's API, which is why your meals stay on infrastructure we own, and why the models keep getting better on our schedule instead of someone else's.
Point the camera at dinner and it answers, end to end, what every other app leaves to you: what this is, how much of it there is, and the full 49-nutrient breakdown. Several dishes in one frame are itemised and totalled separately. When it isn't confident it offers candidates instead of bluffing — and if you point it at something that isn't food, it says so rather than inventing a meal. No camera to hand? Type what you ate and the same breakdown comes back.
Ask a general chatbot what to eat and you get the paragraph everyone gets. Ours was tuned for one field — and at run time, for exactly one person: your profile, your goal, what you have eaten today and how that sits against recent weeks, and the signals coming off your wrist. It holds your hard constraints across the whole conversation — allergens, pregnancy, the foods you have ruled out. Supplement advice arrives as specifications and strength of evidence, never a brand it wants you to buy. And it was trained to refuse invented nutrients and pseudo-vitamins rather than play along.
AI watches your numbers around the clock; a dietitian steps in when it actually matters. Every Delemma user has a dietitian team — at no cost.
Nutrition management, not medical care — no diagnosis, and no substitute for professional medical advice.
We believe technological progress shouldn't cost the Earth. Delemma is engineered from the ground up as an eco-friendly AI agent. By optimizing our inference architecture, we cut energy consumption drastically compared to monolithic LLMs, allowing us to offer a sustainable free tier for everyone.
General-purpose giants burn a staggering amount of compute to answer a question about lunch. Ours are small, nutrition-specialised models — a fraction of the footprint, with the expertise concentrated exactly where it matters.
Photo parsing runs on lightweight nodes close to you; the heavier reasoning only wakes when a question genuinely needs it. Most of what you ask never troubles a large model at all.
We cache nutrition embeddings. When your intake doesn't fundamentally change, the AI doesn't re-compute. BMR/TDEE math runs purely on-device with zero network energy.
Delemma launched on the App Store on Jun 21, 2026. Both models — vision and reasoning — are trained, shipped and serving real users; TestFlight beta continues to run in parallel.
Four screens, one loop. Log a meal, see the gap, get the move, close the gap.
A handful of testers running the loop for a few months. Different bodies, different goals, same pattern.
Every meal looks like a dilemma. Add the prefix and it stops being one — the way you de-bug code, you de-lemma a decision.
Delemma is live, the whole stack is ours, and it keeps evolving. We're open on two fronts.
Two models we trained ourselves, the 49-nutrient ledger, the live biometric pipeline, and the reasoning that ties them together — all built and run in-house, and all in users' hands today. If you invest in health or in AI infrastructure and this is your thesis, we're open to investment and strategic partnership conversations. An email is the whole first step.
Run a nutrition clinic, a hospital nutrition department or a dietitian practice? You can manage your own clients on Delemma. What you get is a console you can actually work in rather than a dashboard to look at: each client's meals with photos, their 49-nutrient attainment, ten vitals, how consistently they've logged, and risk flags already sorted by priority. Leave feedback on one specific meal and it reaches the client attached to that plate. Messages go out over in-app, SMS, email or push — automatically in each client's own language.
Investment enquiries and clinic onboarding both start with an email.
Most health apps stop at calorie counting. The rest demand you read the literature. Delemma does the reading, runs the loop, and hands back a single next move — backed by the real numbers from your day.