Evora.group > Data, AI & Automation

Data, AI & Automation

Put data, AI, and automation to work in operations

You are accountable for results, not demos. We find the places where data, AI and automation actually improve the work, then build them on Microsoft and ServiceNow, measure the outcome, and stay to run it. The test is never how clever the pilot looks; it is whether the operation got faster, clearer or more reliable.

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The challenge

Why do AI and automation stall as pilots?

The pilot impresses and never reaches production. Data is scattered, so the model or the report cannot be trusted. Automation gets bolted onto a broken process and just makes the mess faster. And nobody agreed, up front, what “better” would be measured against.

The result: a graveyard of proofs of concept and no real change in how the operation runs.

The Transformation

What changes with Evora?

How Evora delivers

From use case to
run-ready automation

1

Advise: Ideation & business processes

We find the use cases where intelligence pays off, check the data and the underlying process, and set the outcome and the baseline before anything is automated.

2

Execute: Implementation

We build on the Microsoft Power Platform and Microsoft Fabric/Power BI for data and automation, and on ServiceNow for workflow automation, fixing the process first, then automating it.

3

Stay: Run-ready operations

We run the automation in production, monitor accuracy and outcomes, and keep it governed and improving as data and conditions change.

What we do

Operational automation on Power Platform and ServiceNow

We automate the repetitive, rules-based work that quietly consumes your teams’ time: data entry, routing, reconciliations, status updates, the steps a person does the same way every time. Built on the Power Platform and ServiceNow and kept governed, the automation runs reliably in production rather than as a fragile script. You free skilled people from routine work, cut the errors that come with manual handling, and get a process that runs the same way every time, day or night.

Data foundation, analytics and reporting on Microsoft Fabric and Power BI

We build the data foundation everything else depends on, so reporting and AI run on numbers people can trust. Using Microsoft Fabric and Power BI, we bring scattered data together, define it consistently, and make it available where decisions are made. Allgeier’s Swiss team has delivered exactly this kind of Fabric and Power BI work, for example a group data project at Thommen. You move from arguing about whose figures are right to acting on one reliable view.

AI-assisted decisions and Copilot enablement

We put AI where it improves a real decision, not where it makes a good demo: surfacing the right information, drafting the routine output, flagging the exception a human should look at. We enable Microsoft Copilot and similar assistants inside a governance frame, so the help is useful and the control is clear. The aim is better, faster decisions with a person still accountable, rather than a black box nobody trusts enough to actually use in the operation.

Process mining and automation-opportunity mapping

Before automating anything, we look at how the process actually runs, not how the documentation says it does, and find where the time, the rework and the bottlenecks really are. That tells us what is worth automating and what should be fixed or removed first. You avoid the expensive mistake of automating waste, and you get a prioritized, evidence-based list of where automation will pay back, ranked by effort and impact rather than by who argued loudest.

Data and AI governance

We make data and AI trustworthy enough to run the business on: clear ownership, accuracy checks, access control, and rules for how AI is allowed to be used. This is what keeps what reaches production reliable and defensible as scrutiny of AI grows. You get the benefit of automation and AI without the risk of decisions made on bad data or models nobody can explain, and you can show regulators and your own board that the controls are real.

Measurable automation outcomes

We tie every automation and AI use case to a metric and a baseline, so you can see what it actually changed: hours returned, manual touches removed, cycle time cut, accuracy improved. Intelligence stops being an act of faith and becomes a line you can point to. That discipline also tells you where to invest next, because you can see which use cases paid back and which did not, instead of spreading effort evenly across everything that sounded promising.

Case Studies

Proof of execution.

Magazine zum Globus AG

Read how Evora supported Globus AG in turning complex operational requirements into governed, reliable execution across systems and daily operations.

“Our collaboration with our colleagues at Allgeier was constructive and always characterized by a positive attitude.”

Giovanni Odoni

– Director IT Business Solutions

95

IT services migrated into the new operating environment.

In 18 months

months full IT independence under high time pressure was achieved.

What was involved

The project involved M365, Azure Cloud, Active Directory migration, tenant cutover, DNS, and selected network services.

95

IT services migrated into the new operating environment.

In 18 months

months full IT independence under high time pressure was achieved.

What was involved

The project involved M365, Azure Cloud, Active Directory migration, tenant cutover, DNS, and selected network services.

Speak with an expert

Define the operating model your teams can actually run.

Tell us where execution stalls, which outcomes matter, and which systems need to connect. We will route your request to the right Evora expert.

Sales Americas

Sales EMEA

Sales APAC

Request a meeting

Tell us your challenge — right expert within 24h.

GDPR compliant. Data never shared.

Request a meeting

Tell us your challenge — right expert within 24h.

GDPR compliant. Data never shared.

FAQ

Questions enterprise leaders ask before they commit.

What is enterprise AI and automation, practically?

Using data, automation and AI to make real operational work faster, clearer and repeatable, measured against a baseline rather than demonstrated in a pilot.

Which platforms does Evora use?

The Microsoft Power Platform and Microsoft Fabric/Power BI for data and automation, and ServiceNow for workflow automation; Copilot where governed AI assistance adds value.

Why do most AI pilots fail to scale?

Scattered data, an unfixed process underneath, and no agreed measure of success. We address all three before automating.

Do you fix the process before automating it?

Yes. Automating a broken process only makes the problem faster. We fix the flow first, then automate what should be automated.

How do you govern AI and data?

With clear ownership, accuracy checks and control over how data and AI are used, so what reaches production stays trustworthy.

What happens after go-live?

We stay. We stabilize, monitor reliability KPIs, and keep improving; across the group, post-go-live support averages about 18 months.

Put data, AI, and automation to work in operations

Trusted by

Why do AI and automation stall as pilots?

What changes with Evora?

How Evora delivers

From use case torun-ready automation

1

Advise: Ideation & business processes

2

Execute: Implementation

3

Stay: Run-ready operations

What we do

Case Studies

Proof of execution.

Magazine zum Globus AG

95

In 18 months

What was involved

95

In 18 months

What was involved

Speak with an expert

Define the operating model your teams can actually run.

Sales Americas

Sales EMEA

Sales APAC

Request a meeting

GDPR compliant. Data never shared.

Request a meeting

Tell us your challenge — right expert within 24h.

GDPR compliant. Data never shared.

FAQ

Questions enterprise leaders ask before they commit.

More Questions?

From use case to
run-ready automation