Transform Healthcare Documents into Actionable Intelligence

You can ask any health related questions in the chat. However, the assistant is intentionally designed not to provide medical advice, risk assessments, diagnoses, predictions, or prognoses.

The assistant provides:

• Structured insights derived from your uploaded data
• Summaries and explanations of your documents
• Information based on general medical knowledge

If you experience symptoms or need medical guidance, you should always consult a qualified healthcare professional.

Many AI chatbots rely primarily on Large Language Models (LLMs). LLMs are powerful general-purpose models that generate responses based on patterns learned during training. While they perform well in many contexts, they have known limitations—especially when used with sensitive health data.

Common limitations of general LLM-based chat systems

• Non-deterministic outputs — LLMs may generate slightly different answers to the same question. They can also produce incorrect or fabricated information that is not grounded in your actual data.
• Context window limits — LLMs process only a limited amount of text at once. If you upload large volumes of medical records, some information may not be fully considered unless special processing pipelines are used.
• Data usage policies vary by provider — Depending on the provider and configuration, user data may be logged, stored, or used to improve services or ad profiling. Policies differ between enterprise and consumer plans.
• Cost and scaling considerations — Processing large cohorts or extensive document collections using LLM-only pipelines can become computationally expensive and may impact response time or cost predictability.

With Shareguard

• Deterministic data evaluation — Shareguard uses structured, rule-based and model-assisted evaluation pipelines to ensure consistent outputs. Identical inputs produce identical results.
• Factually grounded outputs — Results are derived directly from your data through verified processing steps, preventing fabricated or misleading information.
• Data sovereignty — Your data is hosted in Switzerland and the EU and is not used to train external models. You can delete your data at any time.
• Scalable architecture — The platform is designed to scale predictably in performance and cost as user numbers and data volumes grow.

Yes.

• Data is encrypted in transit and at rest.
• Health data is hosted in Switzerland and the EU, which maintain equivalently strong data protection standards and adequacy frameworks.
• You remain in control of your data and can delete some or all of it at any time.

Shareguard combines multiple state-of-the-art methods and certified models, each optimized for specific tasks. For competitive and intellectual property reasons, we do not disclose detailed technical specifications, as elements are subject to patent application.

The chat interface is the first feature of our product (MVP).

Planned and potential future features include:

• Cohort analysis and comparison
• Matching eligible patients to actively recruiting clinical studies
• Sharing relevant scientific publications
• Population health analytics
• Signal detection and trend monitoring

We prioritize new features based on customer demand.
Please share your feedback at info@shareguard.health.