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valiss AI
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Consulting & custom projects

We find the use case. Then we build it.

Most companies have heard that AI can save time. Fewer know where that holds true for them specifically. We help companies and organisations find the work where AI genuinely moves something, then build the systems that deliver the result in daily operations.

15%

Average reduction in operating costs across our projects

  • We measure the baseline first, so the saving can be checked afterwards.
  • We build inside the systems you already run instead of adding another layer on top.
  • We put a pilot into real use early, so you see the result before the larger investment.
  • You own what we build. No lock in to a platform you cannot leave.
Two colleagues walking through a workflow together at a desk
Why it works

We start in operations, not in the technology.

An AI project rarely fails because the model is too weak. It fails because nobody asked where the hours actually go. So we map the workflows and do the arithmetic before we build anything. Sometimes that ends in a small system that removes a manual task. Sometimes it ends in a recommendation not to bother. Both are a useful answer.

What we do

Four kinds of work.

Almost every engagement starts with a mapping exercise. From there you decide how far to go.

Mapping

Where does AI make sense for you?

We walk the workflows with the people who run them and find where the time goes. Every opportunity gets an estimate for saving, complexity and risk, so you can prioritise on numbers rather than instinct. The deliverable is a ranked list you can act on, with or without us.

Custom projects

Systems built for your actual work

When the off the shelf tools miss, we build what does not. Case handling that reads and sorts incoming documents. Reports that assemble themselves. Phone and inbox answered automatically outside office hours. All of it built on top of the systems you already use.

Integration

Into the daily operation

A system only saves anything once people use it. We connect it to your CRM, calendar, phone and inbox, and train the staff who will work with it. Short onboarding, concrete workflows, and a clear rule for when a human takes over.

Operations

We stay until it runs

AI models change, and so does your business. We monitor that the system still answers correctly, adjust as requirements shift, and report on the numbers the project was set up to improve.

How it runs

Four steps from first call to production.

We keep the engagement short and the burden of proof on us. There is an exit point after every step.

  1. 01

    Discovery call

    One hour where we hear about the business and tell you honestly whether we can move anything. If the answer is no, we say so.

  2. 02

    Mapping

    Two to three weeks walking the workflows, doing the arithmetic, and delivering a ranked list with an estimated saving per opportunity.

  3. 03

    Pilot

    We build the top item on that list and put it into real use with real data, so the saving can be measured rather than claimed.

  4. 04

    Rollout and operations

    If the pilot works, we roll it out to the rest of the organisation and keep it healthy. If it does not, we shut it down and move to the next opportunity.

When it fits

It usually makes sense if some of this sounds familiar.

A team spends many hours a week moving information between systems by hand.

You get more enquiries than you can answer, and most of them are about the same few things.

You have tried an AI tool, but nobody uses it because it does not fit the workflow.

You are sitting on data you know holds value, but nobody has time to look at it.

You need to grow without hiring proportionally more administration.

You need a clear position on how AI is used internally, before somebody uses it badly.

Let us find out whether there is anything to gain.

A discovery call costs nothing, and we say so if we cannot move anything for you.