How is custom software cheaper than hiring an agency?

AI now does most of the build, so a custom tool typically costs a fraction of what an agency would charge - often up to 20× less. An agency's price pays for a whole team's hours and months of work; with AI, one person can deliver the same tool in a fraction of the time.

How long does it take to build?

Weeks, not months. You get a working prototype on your real data within days, then a production tool tuned until it disappears into the routine - saving hours every week once it's live.

Do I own the software, or is it a subscription?

You own it outright - the code, documentation, and keys, built on a standard, well-documented stack any developer can maintain. No monthly SaaS fees, no vendor lock-in.

What kinds of tools can you build?

Custom internal tools, workflow automation that removes repetitive busywork, tools that turn your documents and data into answers, and honest AI advisory on where AI actually pays off.

Small and medium businesses that have outgrown spreadsheets and off-the-shelf SaaS but don't want the cost or overhead of a full agency. Remote, working with clients worldwide.

Who actually builds it?

Valters Cakss - an AI Solutions Architect with nearly six years leading delivery at Scandiweb, most recently as AI Competence Center Lead. One person, end to end: the person you talk to is the person who builds.

What about changes and maintenance later?

You own the code outright, so there's no lock-in - it's yours to keep. For changes, improvements, or ongoing support, you work directly with me.

What is an AI solutions architect, and when does a business need one?

An AI solutions architect takes a messy business problem and turns it into one tool that fits how you actually work.

An AI solutions architect translates a business problem into a working system. The job is not to write as much AI as possible - it's to decide what to build, what to buy, and what to never build at all, then deliver the smallest tool that actually solves the problem.

It's a role that sits between "I know my business has a bottleneck" and "here is a tool that removes it." Most small and medium businesses don't need a data science team or a software department. They need one person who can hear the problem, work out whether AI is even the right answer, and ship something that fits how they already work.

What an AI solutions architect actually does

The title sounds abstract, so here is the work in plain terms.

Understands the problem before the technology. The first job is to sit with the actual workflow - the spreadsheet everyone hates, the report that takes a day to assemble, the inbox no one can keep up with - and find where the time really goes.
Decides what to build, buy, or skip. Sometimes the answer is a custom tool. Sometimes it's a setting in software you already own. Sometimes the honest answer is "AI won't help here, don't spend money on it." Knowing the difference is the value.
Designs the system, not just the model. A working tool is data, interfaces, permissions, and the boring plumbing that makes it reliable - not a clever prompt in isolation.
Builds it and stays accountable. In my case the same person who scopes the problem also builds the tool and hands over the code, so nothing is lost in translation between "what was promised" and "what was delivered."

The architect's most underrated skill is restraint. Deciding what not to build keeps a tool small, cheap, and maintainable. A feature you never add is a feature that can never break.

The honest first call on any need: build it (nothing fits), buy it (good SaaS exists), or skip it (not worth it yet).

How it differs from a developer or an agency

A developer builds what they're told to build. An agency assembles a team - project manager, analyst, designer, developers - and bills for the layers and the handoffs between them.

An AI solutions architect collapses that into one line. The same person hears the problem, decides the approach, and ships the result. There's no telephone game between the person who understood the need and the person writing the code, because they're the same person.

That matters most for small and medium businesses, where a misread requirement isn't a change request - it's weeks and budget you don't have.

When does a business need one?

You probably need an AI solutions architect when:

You've outgrown spreadsheets and off-the-shelf SaaS, but a full agency is too much cost and overhead for the problem.
A repetitive task eats hours every week - copying data between systems, hand-assembling the same report, triaging the same kinds of messages.
You have documents or data you can't get answers out of fast - contracts, tickets, feedback, records sitting in folders no one can search well.
You're being sold "AI" and can't tell what's real. An architect's first job here is honest advisory: where AI actually pays off for you, and where it doesn't.
You want to own the result, not rent it - the code, the documentation, the keys, on a standard stack any developer can maintain, with no monthly SaaS fee and no lock-in.

When you don't need one

Just as important: if your current tools fit and your team isn't losing time to busywork, you don't need a custom build. If a cheap, well-supported SaaS product does the job, use it. A good architect will tell you that rather than sell you something - because the goal is to solve the problem, not to ship code.

The short version

An AI solutions architect turns a business problem into a working system, and is judged on the system working - not on how much was built. For an SMB, the right time to bring one in is when the cost of working around a tool has grown larger than the cost of building the right one. That threshold is far lower than it used to be, because AI now does most of the build.

If you've been working around a bottleneck instead of through it, start a project and we'll look at the actual workflow first - no commitment until the scope and price are fixed.