Practical AI systems today,a resilient business tomorrow.

Jutro builds AI systems for real business problems and tests them in your daily work before anyone scales them. If AI is not the right answer, we tell you.

How we workBook a call

Jutro is Polish for tomorrow. The work starts today.

We do not predict tomorrow. We fix what matters now and help you get ready for what changes next.

Today

Make the business work better.

Improve workflows and decisions, remove avoidable friction and build the simplest system that creates measurable value.

Tomorrow

Protect what keeps it valuable.

See where AI may change client expectations or make a capability easier to copy, then test the options worth having.

The tomorrow lens is being tested through commercial client work. It is not yet a standard Jutro offer.

You work with two people, from the first call to the final decision.

  • Philip Müller, with long hair and a slight smile

    Philip Müller

    Partner

    Helps new clients get started and sees each project through to go-live.

    Mario
    He will hold me to the date I promised you.

    Project plan8 weeks

    Pilot: quote assistant · Jutro's Client

    Week12345678910DiscoveryBuildTestGo-live
    1. Philip set go-live for Fri 27 Feb.
    or drag it
  • Mario Leśniewski, smiling with his chin resting on his hand

    Mario Leśniewski

    Founder

    Leads every project: discovery, build, test and the decision to scale, revise or stop.

    Philip
    He will ask 'why' five times. It saves you money.

    Recording00:12

    First call · Jutro's Client

    Topic: We need AI in our company. Everyone has it now.

    1. Client

      We need AI in our company. Everyone has it now.

    2. Mario

      Why?

    3. Client

      Because our competitors use it.

    4. Mario

      Why?

    5. Client

      They win clients we used to win.

    6. Up to here, most companies have the same journey. Pick one:
    7. Mario

      Why?

    8. Client

      They quote a new part in two days. We need two weeks.

    9. Mario

      Why?

    10. Client

      Every drawing waits for Thomas to estimate the machine time.

    11. Mario

      Why?

    12. Client

      Only he remembers which old parts are like the new one.

    13. Call summary: next step

      AI finds the most similar past parts and their real machine times. Thomas checks the estimate and signs it.

    PhilipTwo weeks → two days. Told you.

More about Mario and Philip
  • Unlock the transformative power of AI for your business.
  • Supercharge every workflow with autonomous agents.
  • Become AI-first in 90 days.
  • 10x your productivity with GenAI.
  • Future-proof your company with a custom AI platform.

MarioOK, but what problem does this actually solve?

Signal to System

From a real business problem to a system that proves its value.

Every project starts with that question. We find the problem worth solving, test the smallest credible response and scale only what proves useful.

One request, step by step. An illustrative example, not a client case.

  1. You bring

    “We need AI in our company.”

  2. Understand the real problem

    Order approvals take too long.

  3. Find the signal and baseline

    Order approvals take 6 days. We want 2.

  4. Choose the simplest credible move

    A shared order queue and simple priority rules. AI does one job: reading the orders that arrive as emails and PDFs.

  5. Test it in real work

    One team, four weeks. Stop if approvals still take more than 4 days.

  6. Decide what comes next

    Result: 2.5 days. Scale to every team.

    ScaleReviseStop

    Approval time in days. Lower is better.

The right next step may be a system, a simpler change or a decision not to build.

Explore how Jutro works

Start small. You decide after each step.

You do not commit to a large programme up front. Each step ends with a recommendation and the price of the next one. Then you decide.

  1. Phase 0, optionalSignal Check

    2k EuroCredited in full to Discovery if you start it within 30 days.

    About to buy an AI tool or start a project for one problem? First we check it against 3 of your finished cases and two short interviews. We compare your option with a simpler one and recommend one way forward.

    You getA Signal Card: our answer with numbers from your cases, the steps in order and what to check before you spend more.

    BuyNot yetSimpler first

    See an example Signal Card

  2. Phase 1Discovery

    From 7.5k Euro

    We start with stakeholder interviews. Then we build an ontology of your company: a map of its processes, people, data and decisions. Next, we show where AI creates measurable value today or resilience for tomorrow, and where it does not.

    You getAn AI implementation strategy for your organisation with scope, tech stack, success measures and estimated cost.

  3. Phase 2Pilot to decision

    Priced after discovery

    A fast pilot on one process, then an MVP in real work. We measure both against the baseline from discovery.

    Then you decide

    ScaleReviseStop

What we have built so far.

Six real problems from five industries. For each one: the problem, what we built and where it stands today.

  1. 01Healthcare

    Oncology reviewers had to piece together fast-moving lung cancer evidence from scattered sources.

    Built
    An evidence navigator with source-linked answers, visible uncertainty and explicit quality limits. A six-person MIT team project; Mario led the strategy and the deployment and built the app.
    Where it stands
    Deployed. Every answer traces back to its source. Clinical judgment stays with the reviewer.

    Deployed MVPPublic capstone

    Read the case

  2. 02Marketing and events

    Contracts and payouts ran through email, spreadsheets and disconnected tools. Outsourcing added about 30% on top of each contract's value.

    We built
    One internal contract-to-payout process, from approved templates to signatures to payout.
    Where it stands
    Completed. The outside firm is fully replaced, and people review the steps that carry risk.

    CompletedAnonymised

    Read the case

  3. 03Customer research

    Weak product concepts used up expensive panel research, or were filtered by intuition alone.

    We built
    An AI-assisted screen that removes weaker concepts before the paid research starts.
    Where it stands
    Completed. Over 100 concepts screened at 98% lower cost than a panel. Human panels stay the benchmark.

    CompletedConfidential

    Read the case

  4. 04Hospitality and entertainment

    Managers planned staffing from experience, calendars and incomplete demand signals.

    We are building
    A demand forecast from traffic, weather and local events that recommends staffing for manager review.
    Where it stands
    In progress. It must beat simple baselines before a live pilot. Managers keep the decision.

    In progress

    Read the case

  5. 05Hospitality and entertainment

    Planning one group event took 15 to 20 minutes of checking availability, activity by activity.

    We built
    A planning board that shows the whole day's availability at once and builds the schedule as the team picks slots.
    Where it stands
    In use. In September: 353 reservations and an estimated 58 to 87 hours saved.

    In useConfidential

    Read the case

  6. 06Home furnishing e-commerce

    Made-to-measure curtains meant a tape measure, a trip to pick fabric and a wait for a visualisation.

    We built
    A wizard that measures the wall from one phone photo and shows the curtains on it, priced and ready to order.
    Where it stands
    Completed. The whole order happens in one flow, at home, without a tape measure.

    Completed

    Read the case
Read the six cases

You do not need to have it all figured out.

Send a note or book a call. We will help you work out where to begin.

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Not a fit for people-replacement work.