Zero-Configuration Retention Intelligence · HIV Programme Intelligence

Your programmes are data rich.
Insight poor.

8,000-line production-grade analytics. Drop standard DHIS2 and EMR exports directly into the platform - no data cleaning, no infrastructure changes, zero patient data liability.

→ Launch live synthetic demo View security architecture

No data sharing agreement needed · Synthetic data available instantly · smartdaas-hiv-validation.onrender.com

27,288
Patients in training dataset
0.772
Model AUC · temporal holdout
55+
PEPFAR countries · target market
<5 min
Time to first insight
Credibility signals
Peer-reviewed preprint · DOI:10.64898
Shadow pilots · PEPFAR implementing partners, Nigeria
Explainable AI · SHAP-powered predictions
Live platform · AUC 0.772 on temporal holdout
The platform

A real tool. Not a concept.

Live and publicly accessible. Upload your programme data - in minutes, SmartDaaS generates a ranked patient list and a weekly outreach plan fitted to your actual staff capacity.

SmartDaaS  ·  Outreach Optimiser
Model loaded  ·  AUC 0.772
Start here
Home
Patient Risk
Programme
Outreach Optimiser
Executive Report
Validation
Facility Intelligence
Cohort Intelligence
Model Transparency
This week's outreach plan
2 workers · 5 days · 3h/day · 30h total capacity
87.8% high-risk coverage
847
Total patients
124
High risk
45
To contact
13.8
Est. prevented
Patient priority list - highest outreach ROI first
RankPatient IDRiskScorePrimary focus
1PT-0041HIGH83.4%Side effects → regimen review
2PT-0039HIGH83.6%Side effects → regimen review
3PT-0031HIGH96.8%Prior interruption → re-engagement
4PT-0018HIGH74.7%TB positive → TB/HIV integration
5PT-0009MED61.2%CD4 below threshold → urgent review
The challenge
"Out of hundreds of at-risk patients and limited outreach staff - who do we contact first?"

Every week, HIV programme teams across sub-Saharan Africa face this question with no tool to answer it. The data exists. The operational guidance does not.

01
1 in 3 patients is lost to follow-up across sub-Saharan Africa - not from lack of data, but from lack of clarity on where to act.
02
$1.4B in PEPFAR funding is at risk annually from preventable patient loss. M&E teams spend more time on reports than on action.
03
No existing tool converts patient risk scores into a capacity-constrained weekly action plan fitted to actual staff hours. SmartDaaS does.
System compatibility

Works with the data your team already pulls.

SmartDaaS natively recognises column names from the major national HIV data systems across sub-Saharan Africa. No reformatting. No data engineering.

Kenya NASCOP
Kenya National AIDS & STI Control Programme
Columns from NASCOP's patient-level export are mapped automatically. Upload your monthly CSV - no renaming required.
✓ Native column mapping
Uganda DHIS2
District Health Information System 2
DHIS2 aggregate and tracker exports are supported. ART cohort data flows directly into the risk engine without transformation.
✓ Native column mapping
Malawi HMIS
Health Management Information System
Malawi HMIS patient-level fields are pre-mapped. Upload the same export your M&E Advisor already runs monthly.
✓ Native column mapping
PHIA Surveys
Population HIV Impact Assessment
PHIA 2020+ wave variables (MPHIA, THIS, UPHIA) are supported for population-level validation without programme-level data.
✓ Native column mapping
Generic EMR export
Any patient-level CSV
80+ column aliases cover common naming conventions across EMR systems used by PEPFAR implementing partners. If your column isn't recognised, it's flagged - not silently dropped.
✓ 80+ column aliases
No API required
Zero integration work
No IT sign-off. No data pipeline. No new systems. SmartDaaS is a CSV upload - just like the monthly report your team already sends.
✓ Instant evaluation
DHIS2 Native API
Any DHIS2 instance worldwide
Connect directly to your DHIS2 instance via the DHIS2 Web API - no CSV download required. SmartDaaS pulls patient data automatically, maps columns natively, and runs the full analysis pipeline.
✓ Native API connection
Evaluating SmartDaaS requires no data sharing agreement. The live platform runs on synthetic data - upload the sample dataset to see a full outreach plan generated in real time, before sharing a single row of patient data.
How it works

From data upload to actionable plan in minutes.

01 - Upload
Your existing export
Upload the CSV your team already pulls every month. No new data collection. No new systems. SmartDaaS works with what you have - and recognises your column names natively.
02 - Analyse
AI scores every patient
The risk engine ranks every patient by likelihood of treatment interruption - with transparent, SHAP-explainable predictions your clinical team can trust and interrogate.
03 - Act
Your weekly action plan
Enter your outreach capacity - staff count, days, hours. SmartDaaS builds the plan: exactly who to contact, in what order, this week, fitted to your actual resources.
Security & Architecture

Engineered to pass institutional procurement audits.

Three architectural pillars that eliminate every blocker between a conversation and a signed pilot agreement.

Pre-Mapped Schema Ingestion
Stop writing data cleaning scripts. Native column aliasing standardises fragmented country-level exports automatically.
NATIONAL_SURVEYS
Direct zero-prep compatibility: MPHIA, THIS, UPHIA population-based surveys - no reformatting.
HMIS_PIPELINES
Pre-configured variable mapping for Kenya NASCOP, Uganda DHIS2, and Malawi HMIS CSV exports. Now supports direct DHIS2 Web API connection - no CSV export required.
COLUMN_ALIASES
80+ aliases covering EMR naming conventions across PEPFAR implementing partners. Unrecognised columns are flagged - never silently dropped.
Zero Data Liability
Engineered to bypass IRB and cross-border data transfer bottlenecks entirely. No PHI ever touches the server.
STATELESS_PROCESSING
Retains zero Protected Health Information or patient PII. All computation is ephemeral - nothing persists post-session.
SHA256_HASHING
All file names and unique identifiers are one-way hashed on import. The original identifier is mathematically irretrievable.
AUDIT_LOGGING
Supabase enterprise audit logging with brute-force authentication protection and automated 4-hour session timeouts.
Real-World Data Resilience
Frontline health data is messy. SmartDaaS doesn't break - it adapts, grades, and recalibrates.
DQ_GRADE
Automated data quality tiering profiles incoming cohorts and assigns a reliability grade before scoring begins.
CAL_METHOD
Dynamic recalibration adjusts the modelling pipeline to the data tier - accurate outputs regardless of clinic environment quality.
SHAP_15_FEATURES
No black boxes. Every patient-level risk score includes a full SHapley Additive exPlanations breakdown - exact clinical factors, fully auditable.
smartdaas · security_spec.py
# SmartDaaS Security Architecture - verified against institutional procurement requirements

PHI_RETAINED         = False       # stateless processing layer
PII_STORED           = False       # zero patient data liability
IDENTIFIER_HASHING   = "SHA-256"    # one-way · irreversible
SESSION_TIMEOUT_HR   = 4           # automated inactivity lockout
MAX_LOGIN_ATTEMPTS   = 5           # brute-force protection
AUDIT_LOG            = "supabase"   # enterprise-grade · full traceability
IRB_REQUIRED         = False       # stateless · bypasses data transfer review
CROSS_BORDER_TRANSFER = False       # no patient data leaves the session

>>> procurement_audit_check()
✓ PHI compliance verified
✓ Audit trail complete
✓ Zero cross-border data transfer
STATUS: PROCUREMENT READY
PREPRINT doi.org/10.64898/2026.05.15.26353325

Built on published, peer-reviewed methodology.

SmartDaaS is not a prototype - it is a validated platform with a published methodology. The underlying model, validation approach, and outreach optimisation algorithm are documented in a peer-reviewed preprint, giving implementing partners and ministries of health the scientific basis to evaluate and trust the tool before piloting.

Read the research paper →
0.772
AUC on temporal holdout Model performance validated on a held-out time window - reflecting real-world deployment conditions, not in-sample accuracy.
27K+
Patients in training dataset Model trained and validated on 27,288 patient records across the target population - not a small academic sample.
15
Clinical features · SHAP-explained Every prediction is backed by an explainable feature contribution - so clinicians see exactly why a patient was flagged high-risk.

The data we had was always there. SmartDaaS was the first tool that told us what to do with it on Monday morning.

Pilot participant

PEPFAR implementing partner, Nigeria · Shadow analytics pilot 2026

Ready to turn your data
into decisions?

Built for HIV programmes, implementing partners, and public health systems.

Shadow analytics pilots currently being initiated with PEPFAR implementing partners in Nigeria.
No disruption. No new data collection. Results within weeks.

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