Healthcare
Anticipate complications. Keep patient data in-house.
Healthcare analytics on a single standard server: predict complications months ahead, with patient data that never leaves your infrastructure.
Clinical anticipation
Complications flagged up to 6 months ahead, as at Grupo SURA.
Patient data stays put
On-premise by design. Medical data remains inside your own infrastructure.
Every score explained
Variable by variable, so a clinician can defend it.
Our approach
Built for what healthcare analytics actually demands.
Runs on your own infrastructure, brings together data held by ministries, hospitals and insurers, and keeps every model auditable.
Anatella | Data prep engine
Break down the silos
Data scattered across ministries, hospitals and insurers, brought into a single view.
Clean and validate at full scale
Incoming records checked across hundreds of millions of new rows a year.
One pipeline, one server
30+ TB of national health data handled on a single standard server, no cluster.
Modeler / Predictive Engine
Find the patients who matter
A small group of chronic patients drives most of the cost. Models spot them before complications set in.
White-box by design
Every variable explained, every weight documented, ready to be audited.
Built-in Drift Report
Flags a model losing accuracy as populations change, before it leads to a wrong decision.
SOLUTIONS
What it looks like in production.
20% fewer newborns in intensive care
Neonatal complications predicted up to 6 months ahead, worth 1,800 lives saved a year. Delivered by a team of 4 in under 3 months.
Over 98% accuracy predicting dialysis-stage diabetes
Cardiac complications are predicted within 6 months with over 97% accuracy.
30+ TB health registry, on one server
400 million new records a year for 47.6 million inhabitants, processed on-premise after a 3-day pilot.
Problems solved
What healthcare organizations fix with TIMi.
Data locked in silos
Patient information sits across ministries, hospitals and insurers, with no single view to anticipate severe cases.
Care that starts too late
Complications are treated once they are severe, when costs and hospital load are already at their highest.
Predictions nobody can explain
A risk score without reasons is hard to defend in front of a clinician, a regulator or a patient.
Sensitive data on third-party clouds
Medical records on external platforms create a regulatory exposure that was never explicitly decided.
FAQ
Common questions.
What is TIMi used for in healthcare?
Health insurers and public health authorities use TIMi to predict severe complications before they occur and to prepare national-scale health data for analysis. Deployments include Grupo SURA (health insurance, Colombia) and the Colombian Ministry of Health (Minsalud).
Can patient data stay inside our own infrastructure?
Yes. TIMi runs on-premise with no external cloud dependency, so medical data stays inside your own infrastructure. Minsalud processes its national health data on a single standard server, without cloud.
Can clinicians understand why a patient is flagged?
Yes. Modeler is white-box: every score is explained variable by variable and can be audited, so it can be discussed with a clinician, a regulator or a patient.
How much health data can TIMi process?
The Minsalud repository exceeds 30 TB and grows by 400 million records a year, on a single standard server. A 3-day pilot was enough to prove it.
How long does a first predictive model take?
At Grupo SURA, a team of four deployed a predictive model in under three months.
Does TIMi support GDPR and AI Act requirements?
TIMi is on-premise and white-box, which supports obligations such as data control and explainability. Compliance depends on each deployment, so we recommend validating your use case with your legal team.
SEE FOR YOURSELF
Don’t take our word for it.
Run TIMi on your own data with a free trial or request a live demo.
