Diabetes Connections | Type 1 Diabetes
Episode: Snap a photo, know your carb count: The story behind SNACQ with founder Aurelian Briner
Host: Stacey Simms
Guest: Aurelian Briner, Founder of SNACQ
Release Date: November 4, 2025
Overview
This episode spotlights SNACQ ("Snack with a Q"), an app designed to help people with diabetes log meals, count carbs, and gain insights into how foods impact their glucose. Stacey Simms interviews founder Aurelian Briner, who was motivated by his wife's Type 1 diabetes diagnosis to create a more intuitive food-tracking experience. The conversation delves into the app's origin story, its core features, accuracy, clinical evidence, user data privacy, and Briner's vision for the future of tech-enabled diabetes care.
Key Discussion Points & Insights
1. Origins and Inspiration (05:02)
- Aurelian Briner describes the origin of SNACQ as deeply personal: his wife’s Type 1 diabetes diagnosis over a decade ago spurred the project. The challenge of matching meals to insulin and managing nutritional information was the catalyst for SNACQ's creation.
- "That's how we got into it initially." (05:02)
2. SNACQ Today — Core Features and Integration (06:17)
- The app enables photo-based carb counting, supplemented by search, barcode/label scanning, and voice input.
- SNACQ integrates CGM (Continuous Glucose Monitoring), insulin pumps, pens, and activity trackers, providing context on how meals, medication, and exercise interact.
- "What SNACQ is best known for is the capability of taking pictures of meals and converting that into nutrient content." (06:17)
- "You are able to connect your CGM, ...some of the insulin pumps or insulin pens ...and activity trackers." (06:43)
3. Practical Workflow — A Day in the Life (08:57)
- Typical user flow:
- Log a meal: Most start by snapping a photo; the system uses AI to suggest components and estimates portion size if the phone supports it.
- Edit as needed: Users can correct or personalize entries — accuracy improves with user input.
- Get feedback: Post-meal, users review glucose trends, in-range times, and can pinpoint how foods (and exercise) affect their numbers.
- "Logging a meal with images is close to 3x faster than it was in January." (09:49)
4. Accuracy and Scientific Validation (10:33, 27:01)
- Accuracy in carb counting is inherently challenging.
- SNACQ is unique in having peer-reviewed studies comparing its results to hospital-prepared meal data and user estimations.
- "We are actually the only commercially available solution which has peer-reviewed accuracy studies on our carb counting..." (10:47)
- Recent randomized controlled trials (RCTs) show SNACQ improves time-in-range outcomes even for users of advanced Automated Insulin Delivery (AID) systems.
- "...still 6% time in range improvement to be gained even on the very latest systems." (27:33)
5. Personalization and Machine Learning (12:38)
- SNACQ adapts to user habits, prioritizing personalization (rather than retraining global models) to improve relevance and speed.
- "The personalization is now much more crucial to the value of this individual user than the overall model training..." (13:13)
6. Data Ownership & Privacy (13:30)
- SNACQ positions itself against "free" data-selling models. User data is not sold, and the app charges a fee to align its financial interests with user benefit.
- "We're very clear that we don't show ads, and then we don't sell the data because our incentives are directly aligned with the benefits from the user." (13:42)
- "If it is free, then we are the product." – Stacey Simms (14:57)
7. Challenges & User Feedback (15:49, 19:43)
- Most difficult foods: Dishes with mixed components (e.g., casseroles) are hardest for both users and algorithms.
- "As more mixed the stuff is, the more difficult it gets — no matter of the type of cuisine." (18:48)
- User-driven development: SNACQ maintains a public roadmap, solicits feature requests, and regularly updates based on user needs.
- "There probably have been thousands of changes which we explicitly did because people asked for it." (19:57)
8. Portion Size Estimation & Technical Needs (18:48)
- Advanced phones can estimate portion sizes volumetrically (3D), but most users must adjust manually when that’s not supported.
9. Personal Story and Outcomes (21:16)
- Briner’s wife gave birth earlier this year; using SNACQ intensively during pregnancy yielded her best-ever glucose management.
- "The outcomes were also noticeable, ...if you really have the willpower and the energy to put into it ...it's unimaginable actually these levels." (22:07)
10. Future Plans: AI Companions & Expanded Support (23:13)
- SNACQ aims to evolve from a digital logbook to an always-available, AI-powered nutrition/diabetes companion, capable of individualized advice and continuous learning, at a fraction of the cost of personal healthcare providers.
- "We see huge opportunity in kind of like AI companions ...which have access to your data ...have basically the knowledge of a nutritionist or even an endocrinologist...and thirdly, basically learn over time." (25:04)
11. Availability & Market Focus (29:37)
- SNACQ’s principal markets: US (over 90% of users), UK, Australia, New Zealand, Germany, Switzerland, Austria.
- No near-term plans for further expansion; small team prioritizing depth of support and local accuracy.
Notable Quotes & Memorable Moments
-
On Inspiration:
"The impetus for SNACQ was that my wife got diagnosed with type 1 diabetes now more than 10 years ago...matching meals is still one of her main challenges." – Aurelian Briner (05:02) -
On User Experience:
"Logging a meal with images is close to 3x faster than it was in January." – Aurelian Briner (09:49) -
On Data and Privacy:
"If it is free, then we are the product." – Stacey Simms (14:57) -
On Food Complexity:
"As more mixed the stuff is, the more difficult it gets — no matter of the type of cuisine." – Aurelian Briner (18:48) -
On AI and the Future:
"We see huge opportunity in kind of like AI companions ...which have access to your data ...have basically the knowledge of a nutritionist or even an endocrinologist." – Aurelian Briner (25:04) -
On Clinical Impact:
"...there's still 6% time in range improvement to be gained even on the very latest [AID] systems." – Aurelian Briner (27:33)
Key Segment Timestamps
- SNACQ origin story: 05:02–06:17
- Core features and integration: 06:17–07:48
- How users interact with SNACQ daily: 08:57–10:33
- Accuracy and peer-reviewed studies: 10:33, 27:01
- Personalization and user learning: 12:38–13:30
- Data privacy and business model: 13:30–15:36
- Challenge of complex foods/mixed dishes: 16:05–18:48
- Role of user feedback and agile development: 19:43
- Personal story—pregnancy and management outcomes: 21:16–22:52
- Vision for future—AI diabetes companions: 23:13–27:01
- Clinical studies, time-in-range improvement: 27:01–29:37
- Availability and focus markets: 29:37–30:54
Overall Tone & Takeaways
The episode is optimistic yet pragmatic, with Briner openly addressing the limitations — both technical and practical — of AI-based food tracking. Both host and guest emphasize transparency, user empowerment, and the rapidly advancing potential of digital diabetes management. The discussion offers an inside look into how lived experience drives innovation, and how technology (especially AI) is closing the gap between “what-ifs” and tangible everyday tools for the diabetes community.
For more information and direct links to the mentioned studies and SNACQ app, visit diabetes-connections.com.
