Consulting that is built to be executed

The problem

Simulation throughput is limited, but nobody can say precisely where the hours go — preprocessing, waiting for data, rework, or tool friction.

Typical situation

Workflows have grown historically around tools and individuals. Effort estimates are anecdotal, handovers are informal, and the same cleanup work is redone in every project.

Our approach

We map the actual workflow end to end — from CAD receipt to result interpretation — quantify effort and rework per step, and identify which steps are candidates for standardization, automation or elimination.

What you gain

A grounded picture of where engineering time is really spent, and a prioritized redesign of the workflow with measurable targets.

Possible first stepA focused workflow assessment on one representative simulation process.

The problem

Everyone agrees preprocessing should be automated; nobody agrees on what to automate first, with which tools, and how to keep it maintainable.

Typical situation

Isolated scripts exist, written by individual engineers, undocumented and fragile. Attempts at larger automation stalled because they were tool projects rather than workflow projects.

Our approach

We rank automation candidates by frequency, effort and stability, define the automation architecture — scripting layers, batch infrastructure, QA gates — and set up a roadmap from quick wins to pipeline-level automation.

What you gain

An automation program with a defensible sequence, realistic effort estimates and an architecture that survives tool updates and personnel changes.

Possible first stepAn automation-candidate review of your most repetitive preprocessing tasks.

The problem

CAD data arrives in a state that forces manual cleanup before any meshing can start — and the same geometry problems return with every release.

Typical situation

Multiple CAD sources, inconsistent modeling practices, unclear requirements toward design departments, and no defined quality gate between CAD and CAE.

Our approach

We define CAE-oriented CAD quality criteria, design the data flow between design and simulation including conversion and validation steps, and specify what preprocessing should receive as input rather than repair afterwards.

What you gain

Less repair work in every project, clearer responsibilities at the CAD/CAE boundary, and data that is fit for automated preprocessing.

Possible first stepA data-quality audit on a current model release.

The problem

The CAE toolchain is a set of licensed islands connected by file exports and engineers copying data by hand.

Typical situation

Preprocessors, solvers, data management and in-house scripts have accumulated over years. Integrations are point-to-point and break silently. Open-source options are unclear.

Our approach

We assess the toolchain against your workflow needs, evaluate commercial and open-source components on technical merit, and design an integration architecture — interfaces, formats, automation hooks — rather than another tool purchase.

What you gain

A toolchain that supports automation instead of preventing it, with clear-eyed build/buy/open-source decisions.

Possible first stepA toolchain review focused on one workflow you want to automate.

The problem

There is pressure to "use AI in simulation", but no clear picture of which applications are real, which are premature, and what data they require.

Typical situation

Vendor claims are hard to verify, pilot ideas are disconnected from daily workflows, and engineering knowledge lives in the heads of experienced engineers rather than in systems.

Our approach

We evaluate AI and agentic applications against your actual workflows — where assistance is credible today, what data and automation groundwork they need, and how human review stays in the loop. We design pilots that attach to real work, not demos.

What you gain

An AI roadmap for engineering that distinguishes today, next and later — and avoids spending on applications the workflow cannot yet support.

Possible first stepAn AI-readiness discussion anchored on one concrete workflow.

The problem

Transformation initiatives produce architecture slides, while the daily engineering work stays exactly as it was.

Typical situation

Digital-engineering goals exist at management level, but the path from current workflows to the target state is undefined, and initiatives compete for the same key engineers.

Our approach

We translate strategic goals into implementation roadmaps at workflow level: sequenced steps, required infrastructure, responsibilities and measurable milestones — each step useful on its own.

What you gain

A transformation path where every stage delivers working improvements, not a big-bang promise.

Possible first stepA roadmap workshop for one business-critical simulation process.