Skip to content
Preventive medicine infrastructure

Fewer heart attacks.Lower cost.More life.

Corpus AI reads fragmented clinical data and estimates each patient's real risk —heart attack, kidney disease, stroke and more— with calibrated probabilities. It prioritizes who to treat today, before the event costs a life and millions.

patients analyzed1M+
AMIs prevented+241
saved (USD)~$1.5M
AMIs per month−20%
Why it matters

The impact of hittingthe targets.

Every clinical target met is a heart attack that never happens. And a heart attack that never happens ripples across three dimensions: it costs less, it preserves years of productive life, and it spares a family a crisis.

Corpus data · real production deployment
+241AMIs prevented
~$1.5Msaved (USD)
−20%monthly AMI incidence

Economic

Each prevented heart attack saves hospitalization, ICU, procedures and readmissions — the cost that weighs most on a payer or provider.

  • Corpus data~$1.5M saved in production
  • Estimated projectionAt 100k members, projected savings scale to millions per year

Health & productivity

241 prevented heart attacks are years of quality life and work that get preserved — for the patient, their employer and the system.

  • Corpus data+241 AMIs prevented in production
  • Estimated projectionYears of productive life preserved per cohort

Emotional wellbeing

A heart attack shakes an entire family. Preventing it averts the emotional crisis — personal, family and social — that no financial dashboard ever captures.

  • Estimated projectionLower emotional burden on the caregiver and the family
Corpus dataEstimated projection

Corpus figures come from a real production deployment (partner withheld for confidentiality). Projections are illustrative estimates, not guaranteed results.

Internationally validated · NIH All of Us (USA)

The same model, validated on another population,with no retraining.

An independent external validation confirms the calibration holds: when the model says 20%, ~20% happens.

626,396US patients
5.8 yearsmedian follow-up
E/O ≈ 0.98expected/observed calibration
18–89years · diverse cohort
The problem

Today's system: fragmented, reactive, late.

Today

Data in silos. Decisions made on incomplete information. Improvised prevention. No follow-up. 70% of healthcare cost stems from chronic disease that could have been prevented.

With Corpus

A unified system that reads any data, computes risk with visible reasoning, generates the plan, and keeps the loop active over time.

Prioritization Engine

Behind the impact, an engine that turns data intoprioritized decisions.

It reads any clinical data, computes risk with visible reasoning, and emits cohorts ready for action. The full mechanics live on their own page.

  • Explainable risk, not a black box
  • Actionable cohorts, not a score to interpret
  • Recomputed with every new data point
Engine output · stratification

One population,four operational decisions.

The engine converts fragmented data into actionable groups. Each cohort arrives with its clinical action, no score to interpret, just execute.

n = 1,248,302 pacientes
Immediate action8.2%
High-risk intervention17.9%
Active chronic management33.6%
Stable monitoring40.3%
0%25%50%75%100%
Cohorte · 01

Immediate action

102,3618.2% · pacientes
acción →Escalate · 24 h
Cohorte · 02

High-risk intervention

223,44617.9% · pacientes
acción →Contact · 7 d
Cohorte · 03

Active chronic management

419,42933.6% · pacientes
acción →Care plan
Cohorte · 04

Stable monitoring

503,06640.3% · pacientes
acción →Passive follow-up

Aggregate proportions across all clinical paths. 30-day window.

The loop

Five components.One single loop.

  1. 01ingestionWe connect any clinical data sourceHL7 · FHIR · CSV · EHR · PDF
  2. 02standardizationWe turn data into clinical intelligencenormalize · dedupe · map
  3. 03risk + explainabilityWe compute risk and explain whyfeature weights · modifiable factors
  4. 04planWe generate the optimal interventionranked by clinical cost-benefit
  5. 05follow-upWe follow the patient over timere-evaluated as risk changes
Leadership

The best talent,concentrated in five roles.

Five complementary roles, operations, technology, medicine, AI. Every clinical decision is signed by someone with medical practice; every technical decision, by someone who has held it up in production.

  • Portrait of Juan Felipe Forero, CEO at Corpus AI.

    Juan Felipe Forero

    Chief Executive Officer

  • Portrait of Santiago Peláez, COO at Corpus AI.

    Santiago Peláez

    Chief Operating Officer

  • Portrait of Juan Bernardo Benavides, Tech Lead at Corpus AI.

    Juan Bernardo Benavides

    Tech Lead

  • Portrait of Juan Esteban Correa, CMO at Corpus AI.

    Juan Esteban Correa

    Chief Medical Officer

  • Portrait of José David Amorocho-Morales, CAIO at Corpus AI.

    José David Amorocho-Morales

    Chief AI Officer

Supported bythe best clinicians.

The physicians of our Advisory Board accompany us throughout the process: they review what we do and safeguard the model's clinical validity and its implementation in the clinical workflow.

  • Dr. Henry GallardoHospital Management · General Director · Fundación Santa Fe de Bogotá

    General Director of Fundación Santa Fe de Bogotá. He brings the perspective of someone who runs a high-complexity hospital: how prediction gets implemented in real institutions without breaking the clinical workflow.

  • Dr. Augusto Galán SarmientoCardiology · Public Health · Former Minister of Health of Colombia

    Cardiologist and former Minister of Health of Colombia. He watches that the model makes sense at health-system scale: populations, insurance, and public prevention policy.

  • Dr. Guillermo OrtizCritical Care · Intensive Care Medicine · Universidad El Bosque · Centro Policlínico del Olaya

    Internal-medicine physician, intensivist, and Latin American reference in critical care. His clinical review keeps the model’s operating bands meaningful for patients who pass through the ICU.

  • Dr. Enrique MelgarejoCardiology · Electrophysiology · Professor Emeritus, Hospital Militar · Former President, Colombian Society of Cardiology

    Cardiologist and electrophysiologist, FACC and FESC. He reviews the clinical validity of the cardiovascular model: that the infarction prediction holds up against real-world cardiology practice.

Next step

Ready to see the platformon your data?

30 minutes with our clinical team. We look at your case. We respond in 2 business days.

What are you interested in?

Pick the option that best describes you and we'll take you to the right place.