AI at Revolution isn’t abstract. It’s built around the real questions production teams ask every day and the manual work that slows them down.
We embed AI directly into Revolution products to help executives get answers faster, production accounting and finance eliminate repetitive work, and operators focus on decisions — not data wrangling.

Revolution’s AI is narrow, intentional, and secure — critical for payroll, finance, and production data.

ProAnalytics (Text-to-SQL) and ProScan are the first steps in a broader AI roadmap focused on:

Our implementation utilizes Llama models via Amazon Bedrock. All data processing occurs within the AWS security infrastructure using enterprise-grade encryption. Per AWS's standard privacy commitment, customer data used for inference is strictly isolated, is not stored by the model provider, and is never used to train or improve the base Llama models.
No. It removes repetitive work (entry, report building) so people spend time on analysis, decisions, and partner communication.
No. ProScan automates entry; ProAnalytics (Text-to-SQL) lets users ask in plain English. Analysts can still go deep when needed.
We currently use LLaMA for speed/accuracy on these tasks. Architecture is swappable if your enterprise prefers another vetted model (e.g., OpenAI Enterprise).
Role-based access, data-source scoping, and audit logs are built in. We follow least-privilege principles.