Enterprise AI consulting, brought down to a workable form.
In enterprise AI consulting we leave behind working output, not slides. We run four defined engagements; each is tied to a set duration, written deliverables and a handover discipline. We start with a Diagnostic, then proceed along the horizon that fits your maturity.
- Diagnostic2 weeks
- Adoption Sprint4 weeks
- Workflow Rewire6-12 weeks
- Agentic Scale8-16 weeks
Diagnostic
With a two-week field + data study we determine your maturity level, the most suitable business scenario and which horizon to start from. The output is a written Diagnostic report and the analysis that supports the decision.
After the Diagnostic
- Horizon 1
Adoption Sprint
Within four weeks we set up a PoC in a single business scenario: working, measured in the field, handed over to the team. The output is the first step from individual use to company practice.
4 weeksLearn more - Horizon 2
Workflow Rewire
Within six to twelve weeks we redesign one end-to-end workflow together with AI; roles, decision rights, measurement and governance included. The output is a redesigned operating rhythm.
6-12 weeksLearn more - Horizon 3
Agentic Scale
Within eight to sixteen weeks we design an agentic system running autonomously on the production line; together with guardrails, observability and governance infrastructure. The output is an auditable agentic system.
8-16 weeksLearn more
The horizontal layer: activation
The four engagements form a sequence; activation is not a fifth step in that sequence but a horizontal layer attached to several steps at once. Formats from ideathon to AI Office Hours are run against the gap the diagnostic points to.
- Ideathon
Surfaces use cases from the field; builds demand from the ground up.
- Hackathon
Produces a prototype working in a real workflow.
- Prompt-a-thon
Builds a shared prompt library with RTCS-G.
- Agentic Jam
Rehearses the agent together with its guardrails and ownership.
- AI Office Hours
A recurring clinic carrying momentum between major events.
The most expensive step is starting in the wrong place.
In enterprise AI, most budgets evaporate on the wrong first step. The right starting point differs from company to company; a free 30-minute discovery call pins down yours.
