Technology & Data

Enterprise systems and data, treated as one problem.

Most modernization efforts fail at the seams — between the ERP and the data platform, between the architecture diagram and what actually runs. We work across those seams, because that is where our experience was earned.

SAP / ERP

Order-to-Cash, pricing and revenue-stream architecture, ERP transformation and migration planning, and integration with surrounding systems — grounded in 20+ years of enterprise SAP, Order-to-Cash, and large-scale ERP program experience across global manufacturing and technology organizations.

Enterprise architecture

Current-state honesty, target-state pragmatism. Architecture that survives contact with real data volumes, real interfaces, and real operations.

Data architecture

Modern data platforms: separation of storage and compute, event-driven pipelines, and models designed for auditability — not just dashboards.

Data governance & quality

Lineage, provenance, and quality controls designed into the data model from day one, so every number can be traced to its source.

Cloud & integration

Cloud-native builds and modernization, APIs, and systems integration between enterprise platforms and modern services.

Decision support

Analytics, scenario modeling, and simulation that put a defensible number in front of the person who has to decide.

The approach behind the stack

The company's founder spent two decades inside large enterprise transformations — the kind where a wrong architectural decision costs years. That experience shapes three habits that customers feel in every engagement:

  • Business outcome first. The system exists to produce a business result. We can articulate that result before we defend a technology choice.
  • Auditability by design. Financial and operational data must be traceable — who, what, when, why. We design provenance into the model rather than bolting on reports.
  • Real volumes, real behavior. Things that work in a demo and fail at scale are defects, not surprises. We test against representative volumes.

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