Microsoft Copilot deployments
Copilot for Microsoft 365 rolled out across departments, with the data labelling, DLP, and adoption programs that make it actually useful in the second month.
Microsoft Copilot, Azure OpenAI, and custom agents — deployed with the data readiness, adoption programs, and governance that make them operate for longer than a pilot.
Six capabilities, applied in whatever combination your organization needs. Every engagement starts with a data-readiness and governance review — we don't deploy models into systems that aren't ready for them.
Copilot for Microsoft 365 rolled out across departments, with the data labelling, DLP, and adoption programs that make it actually useful in the second month.
Purpose-built agents for procurement, HR, field operations, and records. Built with Power Platform governance you can audit and retire.
Custom applications on Azure OpenAI — RAG over your content, document understanding, structured extraction — inside your tenant, under your controls.
Microsoft Purview, sensitivity labels, and content cleanup so your Copilot doesn't surface the last decade of HR PDFs to the wrong person.
Model registries, evaluation pipelines, prompt ledgers, and the review cadence your audit, legal, and privacy teams need before licence renewal.
Champion networks, role-specific playbooks, and the kind of measurement that tells you whether Copilot earned its licence cost this quarter.
Every enterprise and department we speak with has a Copilot pilot story. Most of them also have a Copilot quiet-shelving story — the programme that went live, surfaced the wrong content to the wrong people, failed an audit question, or simply failed to produce a weekly metric anyone could defend.
The pattern is consistent. Pilots succeed because small, motivated teams work with curated data. Rollouts stumble because the data was never cleaned, the adoption plan was a training deck, and the governance was a single-page AI policy signed by the CIO nine months before anything shipped.
Walvis is built for what comes after the pilot. We take over rollouts that lost their sponsor, we re-plumb the data-readiness work that got skipped, and we build the governance artefacts — model registries, evaluation pipelines, prompt ledgers, retirement criteria — that let your AI programme survive its first board review.
The quiet work is the work. We do it in-house, with cleared staff, on your tooling, with weekly demos. The AI can be exciting. The delivery should be boring.
The licence is the cheapest part. Value comes from data readiness, adoption, and governance — three practices that Microsoft partners talk about on a slide and few actually deliver. We start with the data your Copilot will touch and the controls your regulators will ask about, then build the rest around them.
We track weekly active use per role, time-to-first-value per cohort, prompt accuracy (sampled and reviewed), and content-surface audits. We retire prompts that fail. We publish what we retired. The numbers go to your sponsor, and we help write the slide that goes to your board.
Yes. Our team holds the security clearances required for Government of Canada environments up to Secret. Engagements in higher-classified enclaves are arranged on a case-by-case basis.
Both patterns are common. Some clients engage Walvis as a specialist unit embedded in a larger programme; others bring us in to run the AI workstream end to end. We are used to operating under someone else's governance model, and we are also used to being the governance model.
Then we tell you. Our advisory practice (Service 04) runs AI readiness assessments that end with a short, honest report — typically three to six weeks of pre-work, a redesigned content-labelling plan, or a pause. It is not unusual for the right answer to be not this quarter.