1
Weeks 1–2
Value Map
Decompose the cost and revenue base and the business processes. Identify the value creation opportunities, then size and rank them.
You getA sized shortlist and a baseline
We partner with CEOs and management teams to reimagine how an AI-native company runs, in both decision-making and operations. As a result, we help you increase EBITDA, release cash and accelerate growth.
Our Approach
Weeks 1–2
Decompose the cost and revenue base and the business processes. Identify the value creation opportunities, then size and rank them.
You getA sized shortlist and a baseline
Weeks 3–8
Data foundation, integration, evaluation. Two to three use cases into your systems, inside your own data boundary.
You getWorking software in your own stack
Weeks 9–12
In production with real users, with in-language training on the floor, because a system nobody uses books nothing.
You getUsers on it weekly, not licences
Beyond
Managed service and cost governance, or a clean handover to your team. Then roll the proven pattern to the next function, site or business.
You getThe second deployment at a fraction of the first
Throughout
Immersive and hands-on AI training for leadership and frontline teams, from executive workshops to role-based sessions, so your people can use, own and extend what we build.
You getA team that can run AI without us
AI Deployment
Linking pin to your management and business
Owns the client relationship and the judgement calls, carries the management conversation, and architects the data and system flow once they understand how your business and processes actually run.
In-region, in-language engineers
Full-stack build: data plumbing, integration, process rework, evaluation, deployment and run. Pods of 3–5 per engagement, staffed against your language and systems.
Digital, data & AI leaders across industries
Fluent in what digital, data and AI can do now, with hands-on experience landing it. Brought in per engagement and embedded in each pod for industry depth.
Explicitly absent — an analyst pyramid · a research lab · a sales organisation · a bench you fund between engagements
The delivery muscle — a standing partnership with a large digital and AI engineering organisation gives us production capacity on demand: hundreds of AI-native engineers reachable per build. Pods run in parallel across several engagements.
Why us
We start with the process, the data and the decisions that make the business run, and rework them before a single model is trained. Consultants redesign the process and walk away; dev shops build software onto a broken one. We carry both ends.
Re-engineer and build.
Stop at any gate and keep everything produced up to that point. We engineer the cost of the intelligence itself, putting the right model at the right price on every use case, so the return in the business case is not eaten by the run rate behind it.
ROI and right model.
Operating partners embedded in your process and senior domain advisors set the direction, while a partnered engineering organisation supplies production capacity on demand, without an analyst pyramid or a bench you fund between engagements.
Right people, right cost.
Global firms compete on brand and dev shops compete on price. Our position is the combination of both: we re-engineer the process and build the software, at dev-shop economics.
Team
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Advisors are brought in per engagement and are not employees of the firm. Roles shown are current positions held independently of VectorOp; no advisor is deployed onto an engagement that conflicts with their employment. Advisor biographies are available in full under NDA.
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