Made in Germany
GDPR compliant
Hosted in EU

Use frontier AI on your most sensitive research. While keeping full control.
A governed layer between your researchers and a curated pool of leading models. Evidence-traced answers, model-agnostic routing, and an on-device mode for IP-critical work. Built especially for regulated, commercial life-science R&D.
Trusted across the life science R&D spectrum
Biomed_Advisor is used by organizations across the entire life science research ecosystem — from pharmaceutical and biotech companies to academic institutes and university hospitals.
The real risk
When researchers can't use AI effectively within approved environments, they often turn to external tools to get their work done.
That's when unpublished hypotheses, internal data, and research protocols start finding their way into public AI platforms through personal accounts, beyond the reach of your security and governance processes.
The result is a growing blind spot around intellectual property and sensitive research.
More restrictions won't solve that problem. Giving researchers a secure AI tool that's genuinely useful will.
One platform, different priorities.
Researchers and leaders look at AI from different angles. Explore what matters most to you—or take a look at both perspectives.
Security & IP sovereignty
Your IP never has to leave the building.
Keep sensitive research context under organizational control while still using the best models.
For R&D leadership
Govern AI without slowing innovation.
Provide Research, Legal, Security, and Compliance teams with a platform they can confidently approve — while maintaining full visibility and control over AI usage.
- GDPR-compliant deployment on highly secure servers in Germany as a dedicated customer cloud
- An on-premises deployment option is planned for organizations requiring complete infrastructure sovereignty.
- Centralized administration replaces unmanaged use of consumer AI tools.
For research teams
Protect your research data and intellectual property.
Leverage advanced AI capabilities without exposing sensitive research content, proprietary know-how, or confidential project information.
- Collaborate with AI while maintaining control over critical research assets.
- Proxy and fragmentation mechanisms protect sensitive information when interacting with external models.
- Apply AI to research projects without moving data outside approved environments.
- External models never receive complete research documents or full research context.
Scientific Quality
Answers you can check, not just trust
In precision research, "probably correct" is a liability. Every output is traceable to a source.
For R&D leadership
Decisions you can defend.
Target selection and study design carry an audit-ready evidence trail this is needed for reviewers, partners, and regulators.
- Reduce the risk of a single invented fact costing years of downstream work.
- Transparent provenance behind translational and pipeline decisions.
- The verifiability your governance and regulatory reviewers expect.
For research teams
Every claim traces to a source.
Outputs are grounded in curated biomedical sources, with the evidence shown. Not asserted with false confidence.
- Synthesis anchored in PubMed, ClinicalTrials.gov, and many more, with explicit citations and verified links.
- Confidence indicators surface weak or conflicting evidence instead of hiding it.
- A multi-model approach independently challenges the answers, reducing single-model blind spots.
Model independence
Never locked to one model.
A curated pool of foundation models, instead of hard-wiring your stack to a single provider's roadmap.
For R&D leadership
Strategic control over your AI stack.
Keep leverage on cost, capability, and geography instead of inheriting one vendor's constraints.
- No single-vendor dependency on pricing, roadmap, or footprint.
- New models are continuously evaluated and integrated, without the complexity of managing a fragmented AI ecosystem
For research teams
Always the best model for the task.
Our orchestration layer assigns the right model to each workflow, combining the strengths of leading AI systems behind a single interface.
- One unified research environment – access AI capabilities through a single platform instead of switching between tools and providers.