Preparing a manufacturing organization for ERP renewal by establishing data ownership, data governance, information architecture and application portfolio analysis before the transformation.
Silmaril / Problems we solve
Start with the business challenge.
You don't need another technology project. You need to solve the problem behind it. These are the five situations we are asked into most often.
01 Five situations
The problems behind the projects.
P·1
Preparing for an ERP transformation
Don't migrate your data problems into your new ERP.
Establish data ownership, governance and information architecture before making one of your company's largest technology investments.
How we build the foundation →P·2
Moving AI into real business use
AI is only as good as the information behind it.
Identify the data that matters and make sure it is usable, understandable and appropriately governed before scaling AI.
How we make data AI-ready →P·3
Responding to EU regulation
From regulatory complexity to a practical roadmap.
Understand what upcoming requirements mean for your business, data, systems and responsibilities, and what needs to happen next.
How we navigate EU regulation →P·4
Making invisible information visible
Turn hidden information into insight.
Use AI and analytics to uncover information and patterns hidden in systems, documents, emails and other unstructured sources.
How we surface hidden information →P·5
Turning an idea into something real
Test before you invest.
Use modern AI-enabled development to turn ideas rapidly into prototypes and MVPs, creating something tangible before committing to a major investment.
See a rapid MVP in the proof →02 Proof
From complexity to practical action.
Core samples from recent engagements.
Using AI to analyze a shared customer mailbox and reveal information, volumes and patterns that had previously been largely invisible to management.
Helping management understand the impact of upcoming EU regulation through focused workshops and translating the requirements into a practical roadmap.
Turning an early-stage business idea into a working MVP using AI-enabled development, enabling rapid learning before making a larger investment.