Have you ever validated your software and AI usage to see if it’s reliable, accurate and predictive?
We examine your existing workflows, software and AI usage and measure whether they are reliable, accurate and predictive. That includes evaluating AI-assisted workflows against applicable professional guidance and best practices.
Where validation shows your software’s default or off-the-shelf AI usage is leaving value behind, we build the solutions.
The business already pays for business software to manage clients and customers and uses a little AI, such as lead scoring or drafting. Nobody has checked whether any of it is reliable or accurate, or whether it adds value.
We build a validation program that assesses how reliable and accurate the tools are against what actually happens. We then build solutions for the problems we find, such as a prediction tested against the software’s default.
A person or team relies on AI tools every day and keeps running through token allowances and subscription limits. Much of that usage is wasteful, probably because they have long repeated context, use the largest model for easy tasks, or repeat the same work more than once.
We design workflows that route tasks to appropriate models, reduce unnecessary context, and reuse results to reduce avoidable AI usage and make subscription limits less disruptive.
The business runs on spreadsheets and email. Customer and client information lives in separate files, scheduling is done by hand, and nobody can say who is about to leave.
We build one system that collects the data, stores it in one place, and uses it to manage schedules, predict which customers or clients are likely to churn so the business can act first, and forecast demand and revenue.
David Endicott. A PhD-trained data scientist with more than 10 years of analytics work and AI focused methods in workforce analytics and customer analytics, including optimization, recommendation systems, and surveys.
info@565Logic.com