From genome to resistance prediction.
The models, pipeline, and platform capabilities behind every BactoAI prediction.
A modern architecture, purpose-built for genomic AI.
Built for clinical labs, researchers, and public health.
Machine learning models trained on curated bacterial genomes.
Compatible with common WGS pipelines and formats.
From upload to prediction in minutes, not days.
Enterprise-grade encryption and access controls.
Downloadable, clinician-friendly PDF reports.
Browser-based interface — no local setup.
REST endpoints to connect existing LIMS systems.
Handles single samples to national surveillance loads.
Export raw predictions for downstream analysis.
On-premises deployment for restricted networks.
Designed with HIPAA / GDPR principles in mind.
Models retrained as new genomic data arrives.
A genomic prediction engine — the diagnostic layer other AMR tools build on.
BactoAI predicts antimicrobial resistance directly from a bacterial genome sequence, before or without a completed lab culture. We are not a lab-logistics or sample-booking marketplace, and not a guideline-based prescribing chatbot. Those tools move samples or protocols faster; BactoAI generates the resistance data point they both depend on.
Route samples to labs faster — but still wait 48–72 hrs for a culture result.
Apply WHO or national decision trees to symptoms — no organism-specific resistance evidence.
Predicts per-antibiotic resistance from the genome in under 5 minutes. Complementary infrastructure both categories can plug into.
For Hospitals
- Earlier antibiotic decisions
- Improved antimicrobial stewardship
- Reduced treatment failure
For Researchers
- Resistance surveillance
- Genomic analytics
- Dataset exploration
For Public Health
- National AMR monitoring
- Evidence-driven policy
- Population surveillance