SCRPT builds operational AI systems for institutions. We design, engineer and deploy intelligence infrastructure for banking, infrastructure and large-scale enterprises.
SCRPT AI is an operational intelligence platform designed for real institutions, not demonstrations or pilots.
SCRPT designs intelligence infrastructure integrating data, models and operational workflows into production environments.
Co-Founder & Managing Director
Former Executive Director, Africa at the Tony Blair Institute, and strategy leader at BP and McKinsey. Tina Runeyi helps scale ventures across the continent through disciplined growth, commercial clarity, and execution.
Co-Founder & Innovation Director
Thando Sangqu operates at the intersection of cultural theory and global markets, translating intellectual frameworks into commercially deployable ideas, ventures, and market-ready solutions.
AI Lead Engineer & Director
Former Principal Data Scientist at McKinsey & Company/QuantumBlack, Dr. Maksud Ibrahimov leads SCRPT’s AI engineering and advanced data systems capability with deep technical and enterprise expertise.
Associate Director
Former BCG Principal and McKinsey leader, Bambanani Mketsu brings deep expertise across finance, technology, and transformation, translating strategic rigour into measurable business outcomes.
Clear identification of high‑impact AI opportunities aligned with institutional priorities.
Production‑grade AI systems integrated into enterprise workflows.
Internal teams trained to operate AI systems sustainably.
A multidisciplinary team combining strategy, data engineering and AI implementation.
The Artificial Intelligence Maturity Assessment evaluates leadership alignment, data infrastructure, governance and operational readiness for AI adoption.
Customer intelligence, credit analytics, fraud detection, and portfolio optimization.
Operational analytics supporting capital allocation, project delivery, and infrastructure planning.
Data platforms and AI systems improving policy execution and service delivery.
Development of a unified customer intelligence layer integrating transactional, behavioral and product data.
AI‑driven risk assessment models supporting improved credit decisioning and portfolio monitoring.
Real‑time anomaly detection models identifying suspicious transactions and reducing financial crime exposure.