Forward-deployed engineering
RLG works with enterprise teams on focused AI engagements. We start with the business decision, available data, accountable people and a measurable acceptance standard.
Map approved data from enterprise systems and documents, with provenance and access boundaries.
Represent the business objects, relationships, rules and actions needed by the selected workflow.
Configure retrieval, reasoning and permitted tools around the task, with human approval for consequential actions.
Work with users through integration, evaluation, training and handover.
Indicative planning ranges below are subject to data readiness, integration scope and the agreed project charter.
Business problem, data inventory, baseline measures and responsibility boundaries.
Acceptance: A project charter agreed by both teams.
One controlled prototype or pilot, evaluation data and human approval flow.
Acceptance: Performance against agreed technical and business criteria.
System connections, user workflows, permissions, logs, training and release plan.
Acceptance: User acceptance testing and a governance review.
Reusable modules, additional teams or sites, and continuing evaluation.
Acceptance: Agreed operational and commercial outcomes at each stage.
Potential scopes include manufacturing knowledge retrieval, inventory and order visibility, equipment maintenance assistance and cross-border enquiry workflows. These examples describe potential engagements, not published RLG client projects.
A proposal can separate discovery and pilot work, implementation, ongoing support and reusable module licensing. Deliverables, customer dependencies, data-processing terms and ownership or licence rights are agreed in writing before work begins.
Discuss your project with RLG