RAG for Internal Use vs Customer-Facing Use: Key Risks for SMEs
Internal RAG is low-risk and high-ROI. Customer-facing RAG needs tighter controls. Learn the differences before exposing AI to clients.
Simple, jargon-free guides to help business owners understand where AI can fit into their existing systems and workflows.
Internal RAG is low-risk and high-ROI. Customer-facing RAG needs tighter controls. Learn the differences before exposing AI to clients.
RAG ROI isn’t about hype—it’s about saved time, reduced errors and faster decisions. Learn how SMEs can measure real business value.
This 90-day RAG rollout plan shows SMEs how to deploy AI safely, build trust fast and deliver real value without over-engineering.
Practical, non-hype AI ideas for scaffolding SMEs—turn inspections, job notes, variations, photos and paperwork into faster admin, clearer reporting and fewer missed actions. Focused on what works with real operational data.
Practical AI use cases for logistics and warehousing SMEs—ops briefings, exception triage, “ask your warehouse” search, document summarisation and customer updates—grounded in your real data, not hype.
Practical AI use cases for farms and food producers—batch/lot traceability search, QC exception summaries, ops briefings, document extraction and audit support. Grounded in your real production data and records, not hype.
Realistic AI use cases for facilities management—asset history summaries, SLA risk reporting, audit pack generation and natural-language queries over jobs, inspections and compliance data.
Realistic AI use cases for field service and trade contractors—job summary drafting, quote assistance, “ask your jobs” search, exception triage and client updates grounded in your real operational data.
Realistic AI use cases for building services contractors—certificate summaries, asset history insights, compliance risk reporting and natural-language queries over jobs, tests and documentation.
Real-world AI use cases for maintenance contractors—asset history summaries, PPM insight, exception reporting and natural-language queries over jobs, inspections and invoices.
How AI helps compliance teams search standards, summarise inspection history and surface risks—without losing control of sensitive data.
Real-world AI use cases for manufacturing SMEs—summarising production history, spotting downtime patterns, improving QC reporting and making operational data searchable.
Realistic AI use cases for property management—summarising inspections, drafting tenant responses, spotting repeat issues and making compliance data easier to query.
Realistic AI use cases for fleet operators—summarising defects and maintenance history, highlighting risk patterns, improving compliance reporting and making fleet data easier to query.
Realistic AI use cases for education—summarising learner notes, drafting communications, improving reporting and enabling secure search across policies and guidance without losing data control.