AI consulting · Gauting near Munich

AI consulting in Munich. We automate your day-to-day work.

We analyse your business and development processes and show where AI measurably helps and where it does not. Afterwards we implement what is worthwhile, with the same team that builds software with AI agents every day.

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Why Viewconic

AI consulting for mid-sized companies, that does not stop at the slide deck.

The market is full of consulting that describes potential and leaves implementation to others. We work the other way round: we only recommend what we would build and operate ourselves.

We implement it ourselves

The same people who document your processes build the solution afterwards. We have to be able to deliver what we recommend, which keeps the recommendation honest.

We work with AI agents every day

We develop customer software every day with coding agents, review chains and automated workflows. What we advise you on, we know from our own operations, not from vendor documentation.

We state the limits

Not every process improves with AI. Where a simple form, a clean database or a clear responsibility achieves more, we say so, even if it does not become an AI project.

Two focus areas

Development processes and business processes. Two starting points, one approach.

Some clients come with a development team that should use AI more reliably. Others come with a business department that does too much by hand. Often it is both.

For development departments and IT

Introducing AI into software development

Licences for Copilot, Claude or Codex are quickly bought. A way of working in which the whole team uses coding agents reliably, without quality and security suffering, is harder.

Assessment: how your team works today, where tickets get stuck, where AI is already in use
Workflows with coding agents, tailored to your stack and your repositories
Rules and project instructions, so that every agent run starts under the same guidelines
Quality gates: tests, reviews and security checks that every change has to pass
Ticket workflows in which agents work through tasks and people approve
Rollout in the team with support during the first weeks instead of a one-off talk

Linked to our AI training for development teams and to the process we work by ourselves: Linked to the process we work by ourselves: AI-assisted software development.

For management and business departments

AI process optimisation in business processes

Putting quotes together, sorting enquiries, extracting data from documents, writing reports: many departments contain routine work that AI can speed up. The question is which work, and at what effort.

Documenting processes together with the people who carry them out every day
Automation potential: workflows that can run without human intervention
Assistance potential: tasks where AI prepares and a person decides
Making local workflows and individual tasks at the workplace more productive with AI
Data protection and hosting: EU data centres, services that do not train on your data, or locally operated models
Integration with existing systems instead of yet another standalone solution

Where a custom application is the better answer, we build it: Custom software built around your workflows, operated from a single source.

Process

From the intro call to a pilot. In four steps.

Each step ends with a result on which you base your decision whether to continue.

01
Intro call
You describe your starting point and goal. We tell you openly whether we can help and what a sensible scope looks like.
02
Process mapping in a workshop
We look at the workflows together with the people who carry them out, in the business department or in the development team, on site in Munich and the surrounding area or remotely.
03
Prioritised starting points
You receive a list of the places where AI helps, each with effort, expected benefit and risks. Plus the places where it does not.
04
Pilot and implementation
We implement the starting point with the best ratio as a pilot, either ourselves or together with your team. Afterwards you decide how to proceed based on results.

Outcome

What you have in hand after the consulting. A working basis.

Not a report that ends up in a drawer, but a working basis for the next decision.

A prioritised list of concrete starting points, each with effort, benefit and risk
A clear statement of where AI is not worthwhile in your case
A recommendation on tools, hosting and data protection that fits your requirements
A pilot proposal with acceptance criteria by which success can be measured

Limits

What we do not do. That is part of the consulting too.

You can recognise serious AI consulting by what it leaves out.

No strategy slides without implementation
No promises of blanket percentage savings
No tool rollout that leaves your team on its own afterwards
No pilot that only works in the demo

Evidence

What AI has changed in our projects. Measured, not extrapolated.

Two effort comparisons from our own development. Our experience: with AI-assisted development we end up at between one third and one fifth of classical estimates. In your case this may look different, which is why we start with the analysis.

A patent management firm in Munich

days estimated without AI assistance

days actually needed

A business application in which we have a stake ourselves

310

person-days estimated the classic way

140–160

hours actually worked

Not a client reference: our managing director has a stake in this product, which is why it appears here without a name.

Case study LeafConnect

Automated workflows in live operation

For a trilingual online shop in regulated retail, bug fixing and SEO optimisation run largely automated. Bugs are only fixed together with a mandatory test, and every SEO change is measured against a control group. An example of what AI workflows look like that can prove they worked.

Read the case study

References

Carl Zeiss
SAP
Munich Re
atra.consulting

Companies our team has worked for, partly before the founding of Viewconic. More under About us and in the case studies.

Read on

Advise, build, train. From the same practice.

Frequently asked questions

What should be clarified before AI consulting. Cost, duration, data protection.

What does AI consulting cost?

That depends on the scope: a workshop on a single process is different from introducing coding agents in several teams. After the intro call you receive a written quote with a fixed scope before any costs arise.

How long does it take to see first results?

The prioritised starting points are usually ready a few weeks after the intro call, depending on how quickly appointments with your specialists can be arranged. A pilot follows in weeks, not months. The specific plan is part of the quote.

How do you handle data protection and hosting?

Before every step we clarify which data is processed and where. Depending on the requirements, we use models in EU data centres or services whose terms rule out training on your data. If data must not leave your premises, we use locally operated models. We state the performance differences between these options openly.

Do we need our own developers?

No. For business processes we implement the results ourselves and can also operate the solution. If you have your own development team, we work together and pass on the way of working, optionally supplemented by training.

Is funding available for AI projects?

Federal and state funding programmes exist for digitalisation and AI projects in mid-sized companies, and their conditions change regularly. Whether a programme is an option for your project is something we discuss in the intro call. We do not replace funding advice.

Where does AI help in your processes? We clarify that in the intro call.

Describe your starting point to us in the intro call. You will learn which starting points we see and what a sensible next step looks like, even if the answer is that AI is not the right tool here.