Stop doing work that AI should be doing for you.
AI should save your business time and money, not create more work. First, we'll find the recurring work that takes up the most time in your business. Then we'll simplify it, automate it, and measure the result.
Bringing AI into your company only makes sense when it solves a real business problem.
Copying between emails, spreadsheets, and systems
Data is manually copied, checked, and passed along. Your team loses time on work that automation can do faster and with fewer errors.
Quotes, reports, and replies are still created manually
People repeatedly search for the same information, create nearly identical documents, and check them before sending. AI can prepare the first draft while a member of your team keeps control and makes the final decision.
AI must not become another experiment without results
Before deployment, we define what should improve: time, cost, error rates, or service speed. If we cannot measure the result, we narrow the project or do not start it.
How can I help you?
Process and AI Opportunity Audit
Find out which process is worth tackling before you spend time or money.
I assess your current processes, identify the AI opportunities with the greatest potential, and prepare a concrete plan. You get clarity on what is worth automating, what should wait, and how we will measure value.
- Processes currently taking the most time
- 3–5 opportunities ranked by impact and effort
- A recommended first process and success metric
- A concrete next-step plan
Automating One Specific Process
One process. One metric. A solution tested on real work.
I design and build an automation around one specific process. I connect it to the tools you already use, test it on real cases, and set up error checks and outcome measurement.
- An automated process connected to your existing tools
- Testing on real cases and error checks
- Before-and-after measurement of time, quality, or cost
- Team training and a safe handoff
AI in Your Team's Day-to-Day Work
Not a one-off demo. Concrete tasks, rules, and work habits.
I show the team where AI fits their real tasks, how to verify outputs, and where the boundaries of safe use are. The goal is not a one-off demo, but new work habits that stick.
- Workshops built around your team's real tasks
- Practical AI use for writing, analysis, and decision-making
- Output review, model limits, and the right level of trust
- Rules for safe use of data and tools
How We Work Together
45-Minute AI Opportunity Diagnostic
In 45 minutes, we walk through one recurring process and assess whether it is worth automating.
First-Step Plan
I propose the first process worth solving, a success metric, security rules, and a realistic rollout path.
Execution
We build the agreed solution, test it on real work, train the first users, and measure its impact.
Handoff
Once the solution works, your team takes it over. If you want to keep going, long-term support remains available.
Most common first step
45-Minute AI Opportunity Diagnostic
In 45 minutes, we'll map one recurring process and assess whether it is worth automating. If it isn't, I'll tell you directly. The diagnostic is free and comes with no commitment.
Find Out What's Worth Automating
Matej Lukášik
Consultant for actually useful AI
I am an agentic AI consultant with 10 years of software engineering experience. I help small and medium-sized businesses find specific places where AI can save time, streamline teamwork, and create measurable value.
I take a practical approach to projects: first, I understand the business problems, processes, and data sources; only then do I choose the right tools. Together we design the first usable workflow, set success metrics, and define safe deployment rules.
My solutions build on experience with LLM systems, RAG, evaluations, AI models, automations, and AI agents. My goal is to deliver a solution leadership understands, the team can use, and the company can keep developing independently.
Frequently Asked Questions
We don't know where to start with AI. Is it worth getting in touch?
Yes. This is the most common starting point. On the first call we look at your processes, data, and the places where the team loses time. The goal is the first process worth solving, not a list of tools.
How long does the first deployment take?
Most first projects move from kickoff to a working solution in 2–6 weeks. A simple automation can be live in days. More complex systems take longer, but you should see progress every week.
How do we know whether AI is creating real value?
Before building, we define the metric: time saved, shorter cycle time, fewer errors, better quality, or faster customer response. If value cannot be measured, we narrow the project or postpone it.
How do you handle data security?
We start with data, permissions, and deployment boundaries. The first version should use only the minimum necessary access, clear rules for sensitive data, and human review where the risk is higher. With security, slower and steadier is better.
Open Agent Threat AtlasDo we need our own technical team?
Not necessarily. I can handle the technical side. Someone technical on your team helps with long-term maintenance and ownership, but the first project can start without an internal developer.
What tools do you work with?
I choose the tool only after understanding the process. Sometimes a simple automation between the apps you already use is enough. A custom AI agent makes sense only for more complex work. What matters is security, operating cost, and whether your team can keep using the solution over time.
What happens after handoff?
Once the solution works, your team gets the operating rules, training, and enough context to use it safely. The goal is capability, not dependency. If useful, we can keep improving the solution together.
Let's start with the process that costs your business the most time.
Most clients start with a 45-minute AI opportunity diagnostic. No commitment, no unnecessary hype.