Adult AI does not work on children. Vital-sign normals shift by age band, dosing is weight-based not fixed, growth-curve interpretation depends on which curve you are on (WHO under two, CDC over two), and vaccine schedules follow ACIP guidance that updates annually. On top of the clinical complexity sit privacy rules that go beyond HIPAA: COPPA for patient-facing apps used by children under 13, state-by-state adolescent consent and confidentiality, and parental access rules that vary by state and condition. Generic healthcare AI engineering applied to a pediatric population is a clinical-safety risk.
Taction Software’s pediatrics AI engineers have built age-banded clinical decision support, weight-based dosing engines, growth-curve modeling, and NICU/PICU early-warning systems integrated with pediatric EHR workflows. Engagements begin with a $45K Discovery Sprint.
Our experts are ready to understand your business goals.
We map your pediatric AI use case, identify age-band and weight-band logic, evaluate COPPA implications if patient-facing, evaluate FDA SaMD risk, and produce a technical architecture with explicit pediatric-safety controls.
We build the inference pipeline with age-banded clinical thresholds, PHI redaction, first end-to-end use case, eval harness skeleton with pediatric-specific test cohorts, and audit logging.
We harden for clinical pilot, validate against pediatric-specific clinical cohorts, prepare FDA SaMD documentation if applicable, and produce clinical evidence and care-package handoff.
For productized sprint pages, see Discovery Sprint, MVP Sprint, and Pilot-Ready Sprint.
Vital-sign and lab interpretation that adapts to age band, including newborn, infant, toddler, school-age, and adolescent thresholds.
Medication dosing engines with mg-per-kg calculation, adult-dose capping, and renal/hepatic adjustment for pediatric pharmacokinetics.
Plotting against WHO and CDC curves with AI-driven anomaly detection for failure-to-thrive, obesity trajectory, and short stature.
Prematurity-corrected vital-sign analytics with ventilator-aware deterioration scoring.
ACIP schedule logic with catch-up rules, automatic IIS sync, and clinician-facing schedule reconciliation.
PHQ-A, CRAFFT, and other validated adolescent screeners with state-aware confidentiality routing for behavioral health, reproductive health, and substance use.
For background, see our coverage of ambient documentation patterns and the healthcare AI use cases 2026 guide.
Hire healthcare AI engineers, LLM engineers, or healthcare UX researchers at $8K per engineer or researcher per month.
For estimates, use the healthcare AI cost calculator.
Discovery Sprint $45K, MVP Sprint $95K, Pilot-Ready Sprint $145K. Full pathway $285K over 24 weeks.
Pediatric clinical normals, dosing, and physiology differ from adults across every age band. An adult-tuned model applied to a 6-month-old will flag normal vitals as critical and miss real deterioration. Pediatric AI requires age-banded thresholds, weight-based dosing logic, and pediatric-specific training cohorts.
Yes. WHO curves for under-two, CDC curves for over-two, and specialty curves (Down syndrome, prematurity-corrected) are part of standard work.
If the patient-facing surface is used by children under 13, COPPA applies in addition to HIPAA. We handle verifiable parental consent, limited-collection patterns, and parental-access controls. For adolescents over 13, state-by-state minor-consent rules apply.
Yes. Prematurity-corrected vital-sign analytics, ventilator-aware deterioration scoring, and NICU-specific eval cohorts are within scope.
Yes. State-by-state minor consent rules for behavioral health, reproductive health, and substance use are encoded into the disclosure layer where adolescent risk screening AI is in scope.
Yes. Every engagement begins with a BAA, with COPPA and state-by-state minor-consent controls layered on where applicable.
Your email address will not be published. Required fields are marked *
Our expert reaches out shortly after receiving your request and analyzing your requirements.
If needed, we sign an NDA to protect your privacy.
We request additional information to better understand and analyze your project.
We schedule a call to discuss your project, goals. and priorities, and provide preliminary feedback.
If you're satisfied, we finalize the agreement and start your project.