Miragon AIAnalyse

analyzrWhich processes do you have, and how do they connect?

analyzr brings your process models from engines, BPM suites and modelling tools into one landscape. AI agents propose how the processes connect, your team decides, and you see what a change affects before you make it.

analyzr-demo.fly.dev/projects/nordwind-handel/review/rel_01M4QR6HPTKSC1A8SZB96GM609
analyzr's review screen: on the left a Camunda 7 model with the message throw 'Rechnung versendet', on the right a Camunda 8 model with the message catch 'Invoice sent', and a side panel with the proposed message link at 73% confidence, its rationale, evidence and origin.Open full size ↗
The review screen of the read-only demo (the UI is in German). A message link from a Camunda 7 model to a Camunda 8 model, proposed at 73% confidence by the demo's simulation agent, which runs without an LLM.

The problem

Your processes live everywhere, their links nowhere

Process models sit in engines, BPM suites, Visio files and in people's heads. Nobody has a reviewed picture of which process calls, messages or starts which, so every change and every migration starts with a guess about what it affects.

Today

  • Models spread over engines, BPM suites, Visio files and people's heads
  • Links hidden in call activities, messages and signals
  • Folders sorted by department, not by value stream
  • A hand-kept map that goes stale with the next change

With analyzr

  • One landscape from every source that exports BPMN
  • Every link proposed with confidence, rationale and evidence
  • Each process placed on a step of your value chain
  • What a change touches, before you make it

Where your processes come from

Import from wherever your processes live

analyzr reads the links standard BPMN 2.0 carries: call activities, messages and signals. Whatever exports BPMN can feed it. Today it is tested on models for Camunda 7 and Camunda 8.

How it works

From scattered models to a reviewed map

analyzr reads models that already exist. It does not mine event logs, read runtime data from your engines or generate BPMN.

  1. Import

    Bring in BPMN 2.0 files (.bpmn, .bpmn2, .bpmn20.xml) or whole folders in the browser, or with the CLI or REST. The folder path becomes the model key.

  2. Extract

    Code without an LLM reads calls, messages, signals, start and end events. It accepts call activities that point to exactly one process and proposes identical message and signal names.

  3. Propose

    AI agents in your MCP client judge the remaining candidate pairs with confidence, rationale and evidence. They also propose a value chain step for each process.

  4. Decide

    Your team sees both models side by side in bpmn-js and accepts, rejects, holds or corrects each proposal.

What your team gets

See what a change affects before you make it

The reviewed landscape shows which processes a change touches, which ones a migration has to move together and which steps of your value chain have no process yet. Every relation and placement records who proposed it, with confidence and rationale, and who decided.

  • RelationsEvery call, message, signal and trigger between your processes, with confidence, rationale and the decision.
  • Value chain placementsEach process on its step of your value chain. You draw the chain in the browser or import it as a .vc.json file.
  • FindingsGaps such as unresolved calls or processes without a value chain step.
  • RevisionsA changed model becomes a new revision. Agents see it again only if its facts changed, and your decisions stay unless an endpoint's meaning changed.
  • REST and MCPThe landscape goes out over REST (OpenAPI 3.1) and to your agents over MCP read tools.
  • Value chain fileThe value chain goes out as a .vc.json file in the format of the public value-chain-modeler.

Human and AI

Agents propose, your team decides

A rule settles what it can without an LLM. Agents propose the rest, and each proposal waits for your team or for an auto-accept rule the project owner set.

  • Agents never decide

    Agents propose links and placements. Their project tokens never get the review scope, and no MCP tool accepts a proposal.

  • No LLM credentials in analyzr

    The model comes with your agent, for example Claude Code on your own subscription or API key.

  • Auto-accept is off by default

    Only the project owner can set auto-accept rules, per kind, tier and minimum confidence.

  • Each pair judged once

    Agents judge every candidate pair once, even with several agents at work. A "no link" verdict stays visible to your reviewers.

Get started

Open the demo in your browser

Nothing to install and no login. The demo project nordwind-handel is a synthetic landscape of 31 models for Camunda 7 and Camunda 8. The demo stops when idle, so the first request can take a few seconds.

Status

Where analyzr stands on 14 October 2026

analyzr 0.1.0-alpha.0 is an early alpha, and the public demo runs the same version.

  • Private repository

    The source (MIT licence) sits in a private repository for now. No release, image or package is published.

  • Local mode only

    analyzr runs with one owner on 127.0.0.1.

  • German only

    The web UI is German only, and the agent procedure asks for rationales in German.

  • A simulated demo

    The demo's proposals come from a simulation agent without an LLM. They show the workflow, not the quality of a model, and we have not published numbers on proposal quality yet.

Map your own process landscape.

Tell us where your processes live today and which change you are planning. Until the source is public, self-hosting goes through us.

Talk to us

A 30-minute first call.