Advisory and roadmap
Clarify the business case, prioritise the workflows worth doing first, and set a release path teams can actually absorb.
Platform expertise / Register
The platforms we are asked for by name.
Aevis plans, configures, integrates, operates and improves the enterprise platforms our clients have chosen. Each entry below is a product the client selects and licenses; what we bring is the design, delivery and operating discipline around it.
- selects and licenses the product
- Client
- engagement models available
- Advisory to managed
- responsibility boundary, in writing
- Agreed
How we work with a platform
The product is bought. The operating model is designed.
Whichever platform is in front of us, the work that decides whether it pays back is the same: understand the process, protect maintainability, connect the landscape and leave something the client can run without us.
Implementation and integration
Configure around agreed processes and connect the systems the workflow needs, while protecting upgradeability.
Administration and support
Keep the instance healthy through structured demand, release management and platform operations.
Adoption and optimisation
Measure how the platform is used, resolve the friction that suppresses adoption, and improve what matters most.
How a platform engagement runs
The same six steps, whichever product it is.
A platform programme fails in the same places regardless of the vendor: unclear ownership, data nobody has audited, and a pilot that was never designed to be able to fail. The sequence below is what we run against that, and it is the same for ServiceNow as for Salesforce.
Platform and AI readiness
What the client already owns, what the release and licensing actually permit, and what condition the instance is in.
Data and knowledge readiness
What content exists, who may see it, whether it is current, and whether anything can be grounded in it safely.
Use-case and value prioritisation
Candidate work ranked by value, feasibility and risk against a baseline, rather than by what demonstrates well.
Architecture and control design
Integration, identity, permissions, approval gates and the audit trail — designed before anything is configured.
Pilot, evaluation and production rollout
Built against real data, evaluated against criteria agreed at the start, and released only if it meets them.
Managed operation and continuous optimisation
Owned on an agreed cadence, with the release, evaluation and improvement cycle that keeps it true after go-live.
Platform register
Featured platforms with dedicated capability pages.
Each platform below has a page setting out the products it covers, what Aevis does around it, how a delivery runs and where the responsibility boundary sits.
ServiceNow
Aevis helps organisations plan, configure, integrate, operate and improve ServiceNow around the way their teams work. The platform is third-party software the client selects and licenses.
Microsoft Azure
Aevis works on Azure day two — the cost, drift, resilience and access position that decide what an estate is actually worth to run. The platform is third-party infrastructure the client selects and licenses, and Aevis takes no margin on consumption.
Salesforce
Aevis agrees the operating model — stage definitions, ownership and what a reported number means — and configures Salesforce to serve it. The platform is third-party software the client selects and licenses.
HCL BigFix
Aevis fixes the estate view a patch figure is a percentage of, then configures BigFix to enforce a scope, an exception policy and a ring model somebody has actually agreed. The platform is third-party software the client selects and licenses.
Splunk
Aevis treats Splunk cost as an architecture output rather than a licence line — deciding source by source what earns full-fidelity indexing, and normalising what does so it can be searched across. The platform is third-party software the client selects and licenses.
Grafana
Aevis starts from your last three incidents rather than from a maturity model — which dashboards were opened, which alerts led to an action, and which signals were needed and missing. The platform is third-party software the client selects, licenses or self-hosts.
Qualys
A scanner measures; it does not remediate. Aevis builds the half that closes findings — asset ownership, a defensible priority order, a route into owned work and verified closure. The platform is third-party software the client selects and licenses.
AI across the platform families
Most of what clients call AI is already in the platform they own.
Each vendor has shipped its own AI and agent capability into the products enterprises already license. The first question is rarely which model to buy — it is which of these the client is entitled to, and whether the data underneath is in a state to support it.
ServiceNow
Otto, AI Agents, AI Control Tower and intelligent workflow.
Microsoft Azure
Microsoft Azure services, cloud agents, and the governance, security, and identity controls that determine whether they are safe to enable.
Salesforce
Agentforce, Einstein, Flow and governed grounding in customer data.
Data foundations
The knowledge, search, integration, analytics and observability technologies underneath all of the above — and the only part of this list that is not optional.
Where Aevis stands
We work around these products. We do not sell them.
Licences, entitlements and subscriptions are the client’s, bought directly from the vendor. Scope and feasibility always depend on the environment and the entitlements already held, which we validate before committing to a design. Nothing on this page states or implies a certified partnership.
Bring your environment
Running something that is not listed here?
That is a normal starting point. Tell us what the platform is, where the work is slowing down and what has to stay authoritative, and we will answer against your environment rather than a product demo.
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