A structured internal methodology that powers our AI Opportunity Sprint, audits, and implementation roadmaps. Buyers do not need to commit to the full AIBA first. They start with a narrower commercial offer and we use AIBA behind the scenes.
Map operations across 4 Engines to understand current state and identify constraints.
Classify constraints as Capacity, Knowledge, Process, or Scale using the CKPS framework.
Develop recommendations using QDOAA: Quick wins, Departmental, Organisational, AI Automation, Advanced AI.
Map implementation to AI types: ML for prediction, Agentic for automation, RL for optimisation.
Every business runs on four operational engines. AIBA analyses each one to find where constraints are limiting growth and where AI can create the most impact.
Sales pipelines, pricing models, customer acquisition, retention, and growth strategies.
Processes, workflows, resource allocation, capacity planning, and operational efficiency.
Regulatory requirements, risk management, audit readiness, and governance frameworks.
Data infrastructure, analytics capabilities, reporting, and decision intelligence.
Every constraint falls into one of four categories. Understanding the type determines the solution.
Not enough people, time, or resources to handle demand.
Lacking expertise, training, or information to execute effectively.
Inefficient workflows, manual steps, or poor system integration.
Current approach doesn't scale with growth. Infrastructure ceiling.