Connect AI to the work that matters.

Start with the workflow, then choose the technology

A model response is one part of a working product. Someone still needs to decide where the information comes from, which actions are permitted, what acceptable output looks like and who handles the exceptions. I connect those product decisions with hands-on implementation.

Useful starting points include document processing, an internal knowledge assistant, a draft-and-review workflow, or a customer setup process that currently requires substantial manual work. These are examples to scope together, not promises about an unspecified system.

What an engagement can cover

We can begin by mapping the current process with its owner: the trigger, users, source material, destination systems, volume and recurring exceptions. From there we compare a simple integration, an AI-assisted step and a more flexible agent where the problem justifies it.

A bounded pilot can include approved data access, system connections, representative examples, human review, failure handling and a documented handover. We agree the actual scope after understanding your environment. Existing engineering, security and domain owners need to be involved where their decisions are required.

The outcome might be a working first version, a decision about whether to continue, or a clearer delivery plan. A pilot that exposes a bad assumption before a larger rollout can still be useful work.

Experience behind this work

At RobosizeME, I am Head of Product & Forward Deployed Engineer, owning company-wide product direction and building in-house AI products and integrations. The work includes making deployment-heavy automations easier for customers to connect themselves.

As co-founder and AI Automation Agency Lead at Lexicon Labs, I led seven engineers and designers across discovery, AI product delivery and scale-up, including document automation and enterprise knowledge systems. My external AI research work for Deloitte also involved evaluating applications, adoption risks and implementation opportunities.

Read the full professional profile for the roles, responsibilities and broader background. These are distinct employment, external collaboration and founder experiences.

What makes a useful first conversation

Bring one process that people actually want to improve. Tell me who uses it, where it gets stuck, which systems are involved and who can decide what a good result looks like. An anonymised example is enough for an initial discussion.

We can discuss a project, a pilot or a longer product mandate. Timing, scope, access requirements and commercial terms are agreed directly. There is no universal implementation price before we understand the work.

Questions before we begin

Can you integrate AI with our existing tools?

We first review the workflow, available interfaces, access permissions and the systems that must remain reliable. My work includes integrations, AI agents and knowledge systems. The appropriate design and feasibility depend on your environment.

Do we need a custom model or a new AI platform?

Not automatically. A useful result may come from an existing tool, an ordinary integration or a bounded AI step. We compare options against the task, quality expectations, operating effort and your team's ability to maintain the solution.

Can we work remotely?

I am based in Olomouc, Czechia, and open to teams worldwide. I work in English, Czech and Russian. We can discuss remote collaboration, necessary workshops and any location requirements directly.