Applied AI — and where it actually pays
Finding the places in your business where AI returns more than it costs, and saying so plainly when it doesn't. Pilots designed to answer a question, not to demo well.
Independent technology consultant · Serbia & Spain
Independent consulting on cloud, machine learning and applied AI. The solution gets designed, then explained to the people who have to sign for it — in plain language, with the economics worked out.
The work
Engineering describes a system. The business decides on an outcome. Most projects stall in the gap between those two sentences — and that gap is where I work. Every proposal exists in both columns at once.
Managed Kubernetes, autoscaled across availability zones
A traffic spike stops costing you a night of downtime — and you stop paying for idle capacity the rest of the year
Speech-to-text and synthesis pipeline, tuned on your own domain vocabulary
Every customer call becomes searchable text, and your agents stop writing summaries by hand
Retrieval layer over your internal document base
New hires find the answer themselves instead of interrupting the one person who knows it
Phased migration from on-premise to hybrid, over two quarters
Capital expense becomes a monthly line you can forecast, defend, and cut
Services
Finding the places in your business where AI returns more than it costs, and saying so plainly when it doesn't. Pilots designed to answer a question, not to demo well.
Transcription and speech synthesis put to work: call analytics, voice interfaces, accessibility, media production. Model selection, tuning, and the pipeline around it.
Architecture and migration for infrastructure that simply has to keep running. An honest assessment of what you have, a plan for what you need, real numbers for both.
Pre-sales and solution design for vendors and integrators: positioning, the technical narrative, and a business case that survives the CFO's second question.
Stack
Seventeen years inside global technology companies — enterprise infrastructure, cloud platforms and machine learning, on the side that has to deliver what was sold. Long enough to know which promises hold after the contract is signed.
How an engagement runs
Step 01 — Assess
A week or two: what you run, what it costs, where it hurts, and what the team already knows but hasn't been asked.
Step 02 — Plan
Architecture and a costed roadmap that separates what to do now, what to defer, and what to drop entirely.
Step 03 — Execute
Hands-on, alongside your team, or reviewing a vendor's work from your side of the table. Whichever the situation calls for.
Radar
Updated automatically · 05 Aug 2026
Infrastructure, applied AI and the security news that actually changes what you should do on Monday. Headlines link straight to the source.
Large language model (LLM) agents increasingly rely on external tools to complete complex real-world tasks. However, reliable tool-use planning remains challenging due to the limitations of…
Read at source →
10 days passed from OpenAI models exploiting JFrog Artifactory 0-day to release of a patch.
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A critical Langflow flaw allowing RCE on default deployments is being exploited, says the CISA
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Anthropic said to be the client wanting to secure rent-a-GPU company's compute resources
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Microsoft says tools cost less than competing ones and outperform them, too.
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Read at source →
A curated digest, not a mirror: headline, source and a one-line summary, with the link going to the publisher.
Contact
A first conversation costs nothing and usually takes half an hour. If I'm not the right person for it, I will say so and point you at someone who is.