intelligence

Independent advisory practice · Melbourne

AI for complex decisions.

Kynexis helps leaders and technical teams decide where to use AI and how to govern its role. We design how AI, evidence and expert judgement come together in decisions that carry real consequences.

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Applied research in Australia
Since 2006
Peer-reviewed publications
100+
Conference presentations
150+
Patents
7

Work with Kynexis

Advisory, education and speaking

Engagements start with a specific decision or organisational problem, an agreed scope and a clear owner.

AI strategy and decision architecture

Review an AI initiative or design how AI should support a specific decision. Clarify the options, constraints and evidence gaps, define what needs validation, and set out who has authority to act.

Organisational Intelligence Audit

Identify where teams repeatedly reconstruct project context or lose the rationale for significant decisions. Select a workflow where AI could help maintain that context and define what a pilot should demonstrate.

Executive education and keynotes

Briefings and workshops for leaders and technical teams on evaluating AI outputs, designing human oversight and applying AI to complex work.

Processing industry consultancy

Independent technical and strategic advice to manufacturers, technology developers and research-led ventures. Assess process and equipment options, review trial evidence, set validation and scale-up priorities, and evaluate pathways to commercial use.

The Hybrid Intelligence Framework

A framework for decisions under uncertainty.

The Hybrid Intelligence Framework (HIF) defines where AI can assist, how teams validate evidence and who is accountable for the decision. It preserves the rationale for later review and handover.

  1. Establish the decision

    Specify the decision, its owner, the available options and the constraints that govern it.

  2. Assess the evidence

    Trace the evidence to its sources, test assumptions and identify uncertainties that could change the outcome.

  3. Decide and document

    Use AI to support analysis. Document the decision owner’s rationale and the next action or validation step.

Application example: an R&D scale-up decision

Illustrative example

A team inherits a pilot process just before deciding whether to scale it up. The trial data are in one place, the reasons for ruling out settings are in meeting notes, and the engineer who led the trials is leaving.

Using HIF, the team traces each option back to the trials, recovers the rationale and identifies one unresolved quality constraint. The engineer accountable for scale-up can then compare the remaining options and choose the next validation test.

Founder and principal

Dr Kai Knoerzer

Process engineer and principal research scientist

Kai trained in process and chemical engineering and completed his PhD in food process engineering summa cum laude at Karlsruhe Institute of Technology. His research spans advanced food processing, numerical modelling and applied AI.

Across two decades of applied research, one question has recurred in process design, validation and scale-up: how should a team act when evidence is incomplete and the cost of a wrong decision is material? Kynexis applies that engineering discipline to organisational decisions and the responsible use of AI.

Kai’s sustained collaboration with AI helped shape the Hybrid Intelligence Framework. The work exposed a practical requirement: teams need to retain the evidence, assumptions and reasoning behind a decision so others can review it and continue the work. That requirement now informs Kynexis’s advisory approach.

Kynexis is Kai’s independent practice. He undertakes its work in a private capacity.

Contact Kai

Discuss an engagement

A short note on the decision or programme of work is enough to begin.

QR code for Dr Kai Knoerzer’s LinkedIn profile