Pronix Information Technologies

Media-break-free Process Automation — from a manual process to an automated, auditable flow

An organization turns a manual, media-broken back-office process into a modelled, automated and auditable flow — BPMN/DMN/CMMN models, custom software, and AI/LLM closing the manual gaps — built and handed over to the team.

Delivery with your own team

A back-office process — case intake, approvals, reporting — runs on email, spreadsheets and re-keying between systems. It is slow, error-prone and does not scale. The organization wants it modelled, automated and auditable, with AI/LLM closing the manual gaps so it runs end to end.

Building blocks

LayerWhat we deploy / do
ModellingBPMN (process) · DMN (decisions) · CMMN (cases) — see Automation
BuildCustom Software Development · Realtime Decision Platform
AI augmentationSovereign AI Platform · alerts via Notification Guard
PeopleProcess Manager · Enterprise Architect
DisciplinesAutomation · Consulting

The result: a process that runs end to end without re-keying — readable models the business owns, every decision auditable, quality held by ISO 9001. → Talk to us

What each stakeholder is really asking

CEO

What does automating this process actually buy us?
Throughput without headcount, fewer errors, and a process that runs the same way every time — with the audit trail to prove it. It turns a manual cost centre into operating leverage. → Automation
We've burned money on automation before — why is this different?
Because we automate a model, not a one-off script. BPMN/DMN/CMMN models survive staff turnover and tool changes, ISO 9001 keeps them improving, and we start with one painful process and prove value before scaling. The asset outlives the project.
Where does the AI hype actually help us?
Narrowly and usefully: AI/LLM closes the manual gaps — reading an email or PDF, classifying, drafting — that used to force a human handoff, raising the automation degree without replacing judgement. Concrete leverage, not hype. → Automation

CFO

How do we avoid paying for custom software that just rots?
Because the asset is the model, not throwaway code: BPMN/DMN/CMMN models the business can read and change, kept correct by ISO 9001, with AI/LLM closing the gaps cheaply. It pays back in staff time and rework avoided, and survives any single implementation.
What is the payback, and how fast?
It pays back in staff time on the manual steps and in rework avoided from errors. We start with the highest-volume, highest-pain process, so the first increment usually shows a measurable saving within the quarter.
Per-task AI/RPA tools bill per run — is this cheaper?
Yes over time: instead of per-seat or per-run SaaS that scales with volume, the models and automation are yours, and the Sovereign AI Platform runs in-house with no per-token bill. Predictable cost as you scale.

CIO

How does it fit our systems without becoming another silo?
It is standards-based (open OMG notations), integrates with your existing systems, and the decision logic lives in changeable DMN tables — not buried in code. Your team can maintain it. → Consulting
Will it integrate with our ERP, CRM and legacy systems?
Yes — it connects via standard interfaces and APIs, with the Realtime Decision Platform handling decision logic and AI/LLM bridging the unstructured edges. It orchestrates what you have rather than replacing it. → Custom Software Development
Who maintains the models and rules after go-live?
Your team — DMN decision tables and BPMN models are readable and changeable by the business; we train your people and document everything. A rule change is a table edit, not a code release.

CISO

Is an automated, AI-assisted process still auditable?
Yes — the BPMN/DMN process stays explicit and logged; the Sovereign AI Platform runs inside your perimeter (no data leaves), with review in the loop. Every step and decision is reproducible for an audit.
Does our data leave the building for the AI part?
No — the Sovereign AI Platform runs LLM inference inside your perimeter; nothing goes to a third-party API. Confidential inputs stay yours. → Digital Sovereignty
How do we control and review AI-made decisions?
AI handles only the fuzzy input; the actual decisions live in transparent DMN tables with review and approval steps where they matter. Every action is logged and reproducible — human-in-the-loop by design.

Project lead

How do we do this without a year-long programme?
We start with one painful, high-volume process, model it, and automate the highest-pain step first — a scoped pilot with a visible result in weeks. Burndown/Gantt and a milestone per increment; you see value before the big spend.
How do you scope something this fuzzy?
We model the current process first (BPMN) — that turns the fuzziness into an explicit map of steps, decisions and media breaks. From there the increments and a burndown/Gantt are concrete. → Rent-a-Process-Manager
What if the process changes mid-project?
Models absorb change better than code: you adjust the BPMN/DMN, not a tangle of scripts. Reversible increments mean a change is a re-model, not a restart.

In-house architect

Won't the AI part turn into an unmaintainable black box?
No — the LLM does only the fuzzy last mile (reading unstructured input, drafting); the process and decisions stay in open, inspectable models you control, and ArchiMate maps where it sits. Augmentation, not a black box. → Rent-an-Enterprise-Architect
Why model in BPMN/DMN/CMMN instead of just coding it?
Because models are readable by business and IT, portable across engines, versionable and auditable — code buries the logic in one implementation. The model is the durable asset; the engine is swappable. → Automation
Will this lock us to one BPM engine or vendor?
No — open OMG standards are portable across engines and the Sovereign AI Platform is self-hosted. You keep the models and can move them. → Rent-an-Enterprise-Architect

How it runs, end to end

flowchart LR
    A["Idea: stop the re-keying"] --> B["Model it (BPMN/DMN/CMMN)"]
    B --> C["Build the automation"]
    C --> D["Close the gaps with AI/LLM"]
    D --> E["Operate under ISO 9001"]
    E --> F["Handover: models you own"]

  • The idea — stop the re-keying

    A high-volume process bleeds time on manual handoffs and media breaks. The goal is flow: automate it without losing control or auditability. See Automation.

  • Model it (BPMN/DMN/CMMN)

    A Process Manager models the process (BPMN), the decisions inside it (DMN) and the non-linear cases (CMMN); an Enterprise Architect maps where it sits in the landscape (ArchiMate) and what it touches.

  • Build the automation

    Custom Software Development turns the models into a running flow; decision logic lives in the Realtime Decision Platform as testable DMN tables — changeable without a code release.

  • Close the gaps with AI/LLM

    Where work used to need a human — reading an unstructured email or PDF, classifying, drafting — the Sovereign AI Platform bridges the gap, media-break-free, with review still in the loop. Exceptions are routed via Notification Guard.

  • Operate under ISO 9001

    The process is documented, measured and continually improved — quality that holds, not just speed. Audit trails are reproducible.

  • Handover — models you own

    The BPMN/DMN/CMMN models are readable and yours; the team is trained to change and run them. The end is a handover, not a dependency. See Consulting.

Indicative phasing (not a commitment)

gantt
    dateFormat YYYY-MM-DD
    axisFormat %b
    section Model
    Discovery            :a1, 2026-01-05, 1w
    Model the process    :a2, after a1, 3w
    section Build
    Build automation     :a3, after a2, 6w
    AI augmentation      :a4, after a3, 3w
    section Operate
    ISO 9001 and handover :a5, after a4, 3w