Sacher AI is a behavioural AI consulting and product partner for health and life sciences organizations, helping teams design, evaluate, and deliver AI systems that drive behaviour change and improve clinical outcomes. The company specializes in GLP-1 and obesity care, combining behavioural science with AI to improve patient engagement, retention, and real-world impact. Sacher AI works across strategy, design, testing, and evidence generation, with a focus on safety and regulatory compliance.
Funding
Funding not disclosed
Founders
Product
Problem
Health technology only creates value if it changes what people do, yet many digital health products fail because they are built without understanding user behaviour, workflow fit, or the psychological drivers of engagement. In GLP-1 and obesity care specifically, more than half of patients stop treatment within the first year due to behavioural factors such as difficult side effects, unrealistic expectations, waning motivation, and everyday barriers, leading to poor outcomes and high churn for providers.
Solution
Sacher AI provides behavioural AI consulting and product partnership for health and life sciences teams, helping them decide what to build, design how it should work, and measure whether it changes behaviour in the real world. The company combines behavioural science with AI to create systems that identify disengagement risk, trigger timely interventions, and personalise support around individual patient patterns, motivations, and psychological profiles. Sacher AI works across the full product lifecycle, from pre-development testing of ideas to post-launch evaluation, and supports teams with strategy, design, delivery, and evidence generation. The company does not own a front-end platform or patient app, allowing recommendations to be based purely on what gives a programme the highest likelihood of adoption and long-term value.
Target Audience
Primary customers are digital health teams building patient-facing or operational AI agents, GLP-1 and obesity care providers needing stronger engagement and retention, and founders or product leaders who need AI strategy, research, or safer delivery of behaviour-change programmes.
Features
- Behavioural intelligence layer that connects fragmented data sources including support tickets, clinical messages, app behaviour, weight data, and cancellation reasons to identify at-risk patients
- Agentic and predictive AI systems that trigger workflows and personalise interventions based on individual user patterns and engagement signals
- Patient-facing AI design with safety review of every conversation, including guardrails to prevent drift into clinical advice and medical device territory
- Pre-build testing methodology ("Before You Build™") that evaluates five key uncertainties: need and adoption, workflow and accountability, action logic, commercial viability, and regulation and governance
- Clinical and behavioural research expertise integrated from the start, including digital phenotyping and personalised intervention design for obesity care
- Evaluation and evidence generation support to strengthen external credibility and meet safety and quality standards