Flovio
    Service · AI-native process

    Design the process as if AI was already here.

    AI doesn't deliver value until it's wired into how the work actually happens. We help leaders re-think entire processes from the ground up, with agents and humans sharing the load and ship the first production agents inside the same engagement.

    What it is

    A new operating layer where agents do real work.

    We design AI-native processes end-to-end: where humans decide, where agents act, what data they share, and how the whole thing is governed. Then we build, deploy and measure the first agents so the design is proven, not theoretical.

    • Process re-design assuming AI agents are a first-class participant.
    • Agent and human responsibilities defined down to the decision and data level.
    • Production-grade agent build on top of your data and tools not a sandbox demo.
    • Governance, evals, guardrails and ROI tracking from day one.
    How it works

    Re-imagine, then ship.

    1. Step
      01

      Re-imagine

      We pick a high-value process and re-design it as AI-native what changes when an agent can do part of the work end-to-end. 3, 4 weeks.

    2. Step
      02

      Build

      We build the first 1, 3 agents to production, integrated with your data, tools and human-in-the-loop checkpoints. 8, 14 weeks.

    3. Step
      03

      Scale

      We harden evals, governance and CI, then hand the operating model to your team to extend across the value stream. 4, 6 weeks.

    Outcomes

    Where the value shows up.

    1. 01

      A live, measurable AI-native process not another PoC parked in IT.

    2. 02

      Production agents your team can extend, observe, and trust.

    3. 03

      A blueprint for re-shaping the next process the same way.

    4. 04

      Leadership clarity on where AI moves the P&L and where it doesn't.

    Client voice
    Every interaction with Flovio reflected the same thing: a team that genuinely knows what they're doing. The planning was meticulous, the execution flawless, and the results spoke for themselves.
    CEOInformation Security Company
    Pricing

    What an AI-native engagement costs.

    Senior, AI-fluent team. We don't bill for training juniors on your problem.

    Re-imagine
    €45, 75k

    Design-only engagement. One process, one workshop-heavy month.

    • AI-native target process
    • Agent / human responsibility map
    • Data & tooling readiness
    • Costed build roadmap
    Most chosenRe-imagine + ship
    €140, 280k

    Design + build the first 1, 3 agents to production. 4, 6 months.

    • Everything in Re-imagine
    • 1, 3 production agents
    • Evals & guardrails
    • Human-in-the-loop UX
    • Ownership handover
    AI-native programme
    From €350k

    Whole value stream re-shaped over 6, 12 months.

    • Multiple agent workstreams
    • Operating-model rewrite
    • Centre-of-excellence build
    • Internal capability build

    All engagements are scoped together. Ranges are indicative the final number depends on team size, timeline, and the systems involved.

    FAQ

    Common questions, answered plainly.

    What does "AI-native" actually mean?
    It means the process is designed from the start for humans, automation and AI agents to operate as one system not a legacy process with an LLM bolted on. Decisions, data and handoffs are explicitly assigned to whichever actor is best placed to handle them.
    How is this different from a typical GenAI pilot?
    Most GenAI pilots show that the model works in a sandbox and then stall on integration, ownership and compliance. We start from the operating process, ship to a real production loop, and define the metrics, evals and human checkpoints before anything goes live.
    Do we need our data to be perfect first?
    No and that's usually the wrong place to start. We scope the smallest data set the use case actually depends on, build the loop on that, and tighten the data layer iteratively as the process scales.
    What about model risk, EU AI Act and governance?
    Built in from day one. Every AI-native process we ship includes documented decision logic, evals, audit trails, human-in-the-loop checkpoints and a risk classification consistent with the EU AI Act.
    Will this leave our team dependent on you?
    The opposite is the explicit goal. Engagements include capability transfer, runbooks and an internal owner; the success metric is your team running the loop without us.

    Want AI that earns its keep?

    Bring us the process where AI should already be paying off. We'll show you what an AI-native version looks like and what it would take to ship it.

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