Put your own data to workand answers arrive fast
I build company AI, IoT and internal systems for manufacturing and logistics, only where it genuinely pays off.
What I build for manufacturing and logistics
At the centre of everything sit your internal systems and the data your company already has. The AI layer goes in carefully and in stages, because that is the only way the investment pays off. Every build starts with an audit, not a tool.
Process and AI opportunity audit
- Use cases ranked by value against cost
- Estimated savings and running costs
- Written up with what not to do, and why
- AI Act and NIS2 compliance assessment
- Fixed price, deducted from the project that follows
AI assistant over company data (RAG)
- Answers from your policies, contracts and documentation
- Every answer shows the source it came from
- Users only see what they are cleared for
Agentic AI for operational processes
- Invoicing, quotes, email, complaints and service tickets
- The agent works through the whole step, not one reply
- A human signs off wherever money is involved
- Live in weeks, not quarters
Industrial IoT, sensors and predictive maintenance
- Sensors and cameras as one source of operational data
- An alert and a dashboard instead of a monthly report
- Drift spotted before it turns into downtime
- Built for temperature monitoring across hundreds of vehicles
Digital twin and operations visualisation
- A model of your operation fed by real data
- Simulate a change before you pay for it
- An overview for management, not just an alarm for maintenance
AI integration into your systems
- Connects to ERP, CRM, MES, SharePoint and DMS
- Works with live data, not an export
- An MCP server as a single interface for AI
- No need to replace software that works
What I work on most
The areas where I most often save time and money for manufacturing and logistics companies
And an interface people will actually use
AI is worthless when employees work around it. That is why I also build websites, portals and mobile apps: adoption is decided by the interface, not the model. Designs start in Figma and get tested on the people who will work in them. For graphics and motion I work with partners I trust.
Not finding what you came for? Tell me what you are dealing with. Either there is a solution for it, or I will tell you straight away that someone else does that particular thing better.
Pricing and process
The development quote follows from an audit done up front and is broken into stages. No hidden items and no numbers pulled out of thin air.
How I price work
How we work together
Included in every project
Who am I
My name is Petr Škoda and I build companies AI that works with their own data. I hold a bachelor's degree in Applied Informatics and I'm currently pursuing a master's in Business Informatics at VŠE – Prague University of Economics and Business, so I look at both sides: what the technology can do, and whether it pays off for the business.
On every solution I put the emphasis on control over data, measurable benefit and life after go-live.
Who I have worked for
From sole traders and small companies to large multinationals. I grew up in the family business Škoda Milan s.r.o., so running a company is somewhat in my blood and I understand what usually separates a software supplier from the business itself. A system has to fit the people who will use it every day.
What I studied
I studied Information Technology at the Secondary Technical School in Písek, then completed a bachelor of Applied Informatics at the Prague University of Economics and Business. I am now continuing with a master in Business Informatics. The combination of technical and economic training means I can pinpoint where an IT solution genuinely helps and where it is unnecessary.
How I work
I make a point of the client understanding what is being built and why. I explain the consequences of each decision, show work in progress, and say so when AI is not worth it and adjusting a process would do. I do the development myself; for graphics, motion design and extra capacity I work with partners I have used for years. You have one point of contact and the responsibility stays with me.
Where I work
I am based in Prague and in Tálín near Písek in South Bohemia. We can meet in person in either region; otherwise I work remotely with clients across the Czech Republic and abroad.
Certificates
Technologies I work with
Does that approach make sense to you?
Tell me what you are dealing with. The intro call is free and without obligation.
I know this works. And here is the proof.
From the brief and the architecture through to results, including the hard parts
Facing something similar?
Every engagement starts with a short call about goals and constraints. Get in touch.
Let's collaborate
Wondering where AI would genuinely help you? Tell me what you would like to know. On the intro call I will tell you whether I can do it and whether it pays off for you.
Frequently asked questions
What companies considering AI ask most often
Where will our data live, and will the model train on it?
The application and the knowledge base can run in your own cloud tenant or on-premise, so the documents stay with you. The language model itself I call through a commercial API (OpenAI, Anthropic, Google) in a mode where the provider does not use your content for training and does not retain it beyond serving the request, with EU regions and a data processing agreement. If you need the data never to leave your perimeter, we can talk about hosting your own AI model.
Do you only use commercial APIs, or can you build your own model?
In most cases I call commercial APIs from OpenAI, Anthropic or Google. It is the fastest and cheapest route and it is enough for most companies. Where the brief demands it, I can host an open-source model such as Llama on your own or on dedicated infrastructure, and build a custom ML model or neural network. It is not the default: an own model means data to train on, hardware to run it and someone to keep it current. Whether it pays off in your case, I will say up front.
How do you stop the AI from making things up?
Answers are grounded in specific passages from your documents and each one shows its source, so anyone can verify it in two clicks. When there is no supporting material, the assistant says so instead of inventing something. Before go-live we run a set of real questions from your company and score the accuracy with numbers, not impressions.
What does it cost to run each month?
Two parts: running the infrastructure, and model usage based on the number and size of queries. You get a concrete estimate for your volume as part of the audit, before anything is built. Once live, I track and report costs so they do not creep up unnoticed.
Who owns the source code and the knowledge base?
You do. Source code, documentation, infrastructure access and the processed knowledge base are handed over on completion. I do not work with vendor lock-in; your internal team or another supplier can take the project over at any point. I design solutions so that even the model can be replaced, because today's best one will not be best in a year.
How do you handle NDAs, GDPR and our IT department?
I sign NDAs as standard, respect internal security policies and handle personal data in line with GDPR, including a processing agreement with the model provider. I work with your IT on deployment, access and operating rules, and I will supply whatever your security review needs from a supplier.
Can you connect to our existing systems?
Yes, that is usually the heart of the job. I regularly integrate ERP, accounting and warehouse systems, SharePoint and DMS, Active Directory and SSO, and third-party APIs. Where no API exists, I design a safe way to get the data out without touching a system that works.
What if it turns out AI is not worth it for us?
Then I will say so. That is exactly why we start with an audit rather than development. Sometimes changing a process or buying a module for a system you already own is cheaper and faster. Delivering something nobody uses six months later is a worse reference than a lost contract.
How long until we see the first result?
The audit takes days. A first pilot in real operation usually four to eight weeks from signing, depending on the state of your data.