Supporting structured, transparent dosing decisions for people using insulin injections — and the clinicians who guide their therapy.
Millions use pumps. Hundreds of millions rely on injections. BolusGuide is being developed to bring transparent, user-controlled decision support to a much larger population that typically lacks access to structured dosing tools.
A new layer of decision support for injection-based therapy.
All values are entered or explicitly confirmed by the user before any decision is made.
Meal and correction support built on configured therapy parameters and visible assumptions.
No automatic insulin delivery, no autonomous therapy, and no hidden system behavior.
Designed for people who rely on injections rather than the integrated support available to pump and smart pen users.
More than 200 million people worldwide use insulin therapy, and the vast majority do not have access to integrated, high-resolution dosing support. For most, daily dosing remains manual, approximate, and cognitively demanding.
Diabetes management requires repeated decisions, sustained attention, and constant vigilance. For people using injections, those decisions are often made manually, using simplified rules or static guidance that are easy to apply, but inherently coarse.
Some tools provide structured dosing tables based on carbohydrate intake. While an improvement, these approaches typically do not incorporate real-time blood glucose or correction logic, and often require ongoing adjustment throughout the day.
Millions of people benefit from advanced dosing support through insulin pumps. Hundreds of millions rely on injections and smart pens without access to the same level of precision.
The underlying therapy model is the same. The level of decision support is not.
BolusLabs exists to address the friction and cognitive load that users experience every day.It does so by bringing deterministic, transparent, user-controlled decision support to injection-based therapy.
Sources: International Diabetes Federation (IDF) Diabetes Atlas, World Health Organization (WHO) – Diabetes
Even with clinician support, many dosing decisions still depend on simplified rules, paper-based guidance, and repeated user interpretation.
Around meals, users must interpret guidance, estimate, and adjust—often repeatedly throughout the day.
BolusLabs is designed around safety, transparency, and real-world use.
The system is designed with a security-first mindset, emphasizing controlled inputs, predictable behavior, and protection of user data throughout the calculation process.
The architecture reflects experience in regulated software environments, where traceability, validation, and system boundaries are critical to safe operation.
The founder brings more than three decades of personal experience managing diabetes, informing both the design decisions and the focus on reducing daily cognitive burden.
A deterministic calculation flow with explicit user control at every step.
The user enters or confirms relevant values such as blood glucose and carbohydrate intake. All inputs are explicitly user-controlled.
The system applies configured therapy parameters to estimate meal and correction dosing. All logic is transparent and consistent.
The recommended dose is presented for user review. No automatic dosing occurs, and all decisions remain under user control.
BolusGuide is designed for real daily routines—helping users move from repeated estimation toward structured, consistent insulin dosing decisions.
Around meals and corrections, users need fast, clear, and reliable decision support—without giving up control.
Every recommendation is visible, explainable, and confirmed by the user.
BolusView is designed to support review of dosing patterns and facilitate structured therapy discussions over time.
Structured data and deterministic logic enable more consistent therapy discussions and adjustments over time.
The clinician layer supports decision quality over time without introducing automated therapy.
BolusGuide is built around deterministic logic, explicit user control, and clear system boundaries—ensuring that every decision remains transparent and user-driven.
All inputs are manually entered or explicitly confirmed by the user. The final dosing decision remains with the user.
Configured therapy parameters, visible assumptions, and explainable outputs form the basis of the system.
No closed-loop control, no automated insulin delivery, and no autonomous therapy behavior.
