AI Solutions

Microsoft 365 Copilot work stays in your Microsoft tenant under your existing data-residency and DLP rules. Custom or open-weight model work is hosted on Trucell Private Cloud or a colocation environment under our ISO 27001:2022 certified controls. Either path is documented up front so legal and security can sign off before the model is connected to anything sensitive.

Most first Copilot rollouts land between four and eight weeks: a permissions and label cleanup phase, a pilot ring of named users, and then a wider release with a usage and licence model. We scope a fixed-price discovery for the first phase so finance can plan against a known number rather than an open-ended consulting bill.

We do not deploy generative AI as the final decision maker in regulated workflows. The pattern is human-in-the-loop with the model surfacing or drafting and a qualified person signing. For clinical workflows, ClariRad QA is the worked example: it flags issues for the radiologist before signature, the radiologist still signs the report. Same pattern applies for invoice approval, contract review, and similar.

Not for most workloads. Copilot and Azure-hosted models consume capacity inside your existing Microsoft tenant. Custom and open-weight models can run on Trucell-managed NVIDIA GPU capacity priced per workload. We only recommend dedicated GPU hardware when the use case (sustained high-throughput inference, strict data-residency on-premises) justifies the capital.

AI that touches clinical reporting, diagnostic image interpretation, or any classified workflow gets a documented classification conversation up front: is the tool assistive or autonomous, what is the risk class, what evidence is needed. Trucell operates an ISO 27001:2022 certified ISMS and an ISO 9001:2015 certified QMS, so the governance posture under the AI work is auditable.

You do. Prompts, model versions, and integration code sit in source control you have access to, with a change record. Trucell can continue to operate the run-state under a managed agreement or hand it over to your team with a documented runbook. Either way the handover is explicit, not "trust the consultant".

Yes. The usual starting point is a discovery week: we sit with one team, watch how work actually happens, and come back with two or three concrete AI opportunities ranked by feasibility and value. From there you pick one. No platform commitment is required until the first opportunity has been worth delivering.