We find every treatment a patient qualifies for, anywhere in the world, and get them into it.
Precision oncology first. Then every disease where the right therapy already exists but the patient never reaches it.
For clinicians, hospitals, and health systems.
A patient gets a genomic report. Then nothing happens.
A dozen handoffs. No one owns the outcome. Patients lose months, and many never reach the therapy they already qualify for. The treatment existed the whole time. The routing didn’t.
Three steps, from a stack of records to a patient in treatment.
Upload the records
Discharge summaries, pathology, imaging, sequencing PDFs. No integration required to start.
Get every option they qualify for
Approved, off-label, expanded access, and open trials, worldwide, each with the eligibility reasoning attached.
Then we get them in
Referral to a site that can actually deliver it, plus paperwork, scheduling, and follow-up on what happened.
One pass: ingest, reason, act.
Messy records, structured case
Records, pathology, imaging, and sequencing PDFs, normalised into one structured case.
Eligibility, not guesswork
Phenotype and biomarkers matched against every therapy and trial. Ranked, with the criteria shown.
Route, refer, follow up
Route to a site that can deliver, draft the referral, map the access pathway, capture the outcome.
Everyone else stops after reasoning. The value, and the data, is in the referral and what happened next.
Not a report. A ranked set of routes, ready to act on.
Approved targeted agent
On-label for this alteration. Available in-country.
Open phase II, 340 km away
Meets all inclusion criteria. Two screening slots this month.
Expanded access, next-gen inhibitor
Sponsor accepts named-patient requests. Import pathway mapped.
Every line carries the criteria it matched on, and the reason the others were ruled out.
Three curves crossed at once.
The unautomatable task, automated
Models can finally read a messy record and reason over eligibility criteria, the task that blocked this for twenty years.
The reports already exist
Genomic testing has moved from research to routine. The reports exist. The follow-through doesn’t.
More options than anyone can track
Targeted agents, cell and gene therapies, and open trials now outnumber any clinician’s ability to keep up.
The science is ready. The routing layer is missing.
Most founders know AI. Few know how precision medicine is actually delivered.
Dr Raju
Physician | Harvard | Fulbright | Public Health | Digital Health, AI & Health Policy | Ex Pfizer, AstraZeneca
Arjun Raizada
AI/ML Engineer | Full-stack engineer with expertise in machine learning, distributed systems, and production AI systems
Sreelakshmi Panginikkod
Assistant Professor | Associate Program Director, Division of Rheumatology, Tufts Medical Center, Boston, MA
Google organised information. Stripe organised payments.
Lind Atlas organises precision medicine.
Every patient, regardless of geography, income, or health system, reaches the right therapy at the right time.