FASTlab — Evidence Intelligence Architecture for Complex Decisions

The problem

Evidence is abundant.
Trustworthy understanding
is not.

Most organisations do not lack evidence. They lack a governed way to interpret it. Programmes generate data. Evaluations produce findings. Dashboards show movement. Research keeps expanding. Lived experience, professional judgement and operational knowledge all matter. But the difficult question remains: what does the evidence justify us saying, doing or deciding?

FASTlab works in the hidden middle — where evidence is framed, appraised, interpreted, challenged and translated into action with an explicit view of confidence, uncertainty and responsibility. FASTlab exists to close that gap by building the evidence intelligence architecture between evidence and action.

We have data but are not sure what it means.

We need to know whether a programme is working — and what the evidence can support.

We need to understand what the evidence can support — and where confidence is limited.

We need to explain our decisions to funders, partners or regulators.

We want to build a more structured approach to evidence.

How we think

Data does not create value until it enters
a governed chain of interpretation,
review and action.

The FASTlab Evidence Chain — the intellectual foundation of every system we build.

Signal

Something reliably detected

Context

Interpreted for this person and setting

Threshold

A rule that explains why it matters

Alert

A flag or escalation prompt

Review

A person interprets the signal

Action

Someone responds meaningfully

Outcome

Understood as useful — or not

Meaningfulness isn't in the data. It's in the interpretation. Every step in this chain is a human judgement — not just a number.

The FASTlab Evidence Intelligence Architecture™

The knowledge architecture
that transforms evidence into
decision intelligence.

The governing principle

Each piece of knowledge has a maintained source record, with its provenance, interpretation and validation status reviewed as evidence and contexts change.

Build carefully. Review continuously. Adapt responsibly.

The FASTlab Evidence Intelligence Architecture™ is not a dashboard, survey, AI chatbot, reporting tool, database or document library.

It is the governed architecture through which evidence becomes trustworthy understanding. It makes visible how questions are framed, evidence is appraised, meaning is constructed, confidence is calibrated and action remains accountable. Claims are designed to be explainable. Recommendations are bounded by what the evidence can and cannot support.

As AI makes it easier to generate confident-sounding answers from opaque reasoning, FASTlab provides the missing trust layer: governed provenance, explicit confidence, human review, challengeable interpretation and audit trails that funders, regulators and partners can interrogate.

The knowledge pipeline

Evidence

Raw observations

→

Meaning

Interpreted significance

→

Construct

Conditions identified

→

Relationships

Intelligence created

→

Decision

Confident action

The design intent is that no object skips a stage. Decisions can be made more traceable back to their originating evidence.

Five core object types

Construct

The enduring conditions associated with value creation — Trust, Vision, Capability, Impact.

Meaning

The interpreted significance extracted from evidence for this context and this person.

Evidence

Individual observations, metrics, statements, documents or data — the raw material.

Relationship

The connections between objects that enable reasoning and intelligence to emerge.

Rule

The translation, confidence and decision logic governing interpretation — making reasoning explicit.

Eight design principles

01Single source of truth

02Evidence before opinion

03Meaning before measurement

04Relationships create intelligence

05Explainable decisions

06Domain independence

07Continuous learning

08Build once. Reuse everywhere.

Application · Built on the Architecture

Project JANUS™ is one application of the FASTlab Evidence Intelligence Architecture™ — not the architecture itself. It applies FASTlab’s evidence interpretation discipline to value creation, programme readiness and stakeholder reporting, and is being developed in collaboration with MCB Business Partners.

Explore Project JANUS™ →

Applications

Architecture
to applications

These projects inform and apply FASTlab’s developing Evidence Intelligence Architecture™. Their questions, evidence types, outputs and stages of development differ; each requires context-specific review and validation.

Value creation · Education · Workforce

Project JANUS™

Applies FASTlab’s architecture to value creation, programme readiness and stakeholder reporting. Project JANUS™ helps organisations ask: is this initiative ready to create value, what evidence supports that claim, and where is confidence limited?

For: Government programs, industry partnerships, workforce initiatives
Evidence: Stakeholder data, program metrics, longitudinal assessment
Decision: Is this program creating real value? What needs to improve?

Explore JANUS → Try the free self-check →

Digital health · Sensor data · Care decisions

Meaningful Measures

Research informing the architecture through sensor-derived health evidence outside hospital — asking which measures matter, in which contexts, at what thresholds, and with what validation before action is justified.

For: Health technology companies, care providers and researchers working with sensor-derived or observational data
Evidence: Sensor streams, clinical data, lived experience
Decision: Is this measure meaningful enough to act on?

Evidence atlas → Evidence translation framework →

Rehabilitation · Recovery · Clinical oversight

REGAIN

In development for post-stroke rehabilitation — exploring how home-based activity, guided exercises, progress tracking and clinician review can support a shared recovery pathway.

For: Stroke survivors, rehabilitation clinicians, health systems
Evidence: Exercise compliance, functional progress, clinical review
Decision: Is this person recovering? When does the clinician need to act?

Explore the REGAIN project →

Education · Energy · Community systems

Complex Systems

Applies the architecture to contested public, organisational and community problems where evidence is fragmented, actors disagree and simple metrics are not enough.

For: Government funders, community organisations, councils
Evidence: Program data, community voice, longitudinal indicators
Decision: Is this investment creating lasting change?

Talk to us →

Work with FASTlab

Three ways to engage

You do not need to adopt the whole architecture at once. The right starting point is one real evidence challenge: a decision, claim, programme, dataset, report or intervention where the meaning of the evidence is unclear, contested or hard to defend.

Offer 01

Evidence Intelligence Reflection

A focused first engagement to identify where evidence is fragmented, overclaimed, unused or unactionable — and what level of confidence is currently justified.

Evidence readiness review
Decision map
Risk and opportunity view
Recommended next steps

Talk to us about a Reflection

Offer 02

Evidence Architecture Build

A deeper engagement to design the evidence-to-action architecture: questions, evidence sources, interpretation logic, confidence thresholds, reporting discipline and review points.

Evidence architecture
Knowledge Object model
Indicators and measures
Decision logic
Reporting framework
Implementation roadmap

Talk to us about a Build

Offer 03

Evidence Intelligence Partnership

An ongoing relationship where FASTlab stewards the architecture, supports interpretation, strengthens reporting and helps ensure the evidence method remains trustworthy as the work scales.

Bespoke application development
Partner data integration
Evaluation and validation
Reporting infrastructure
Future commercialisation pathway

Talk to us about a Partnership

Proof of capability

Work that generated
real evidence

Selected projects that inform FASTlab's Evidence Intelligence Architecture, with development status noted where relevant.

Digital health · HMRI funded

REGAIN — Stroke Rehabilitation

Challenge: helping stroke survivors, carers and clinicians understand progress and support needs between clinical visits.

FASTlab approach: contributing co-design and evidence interpretation to a rehabilitation platform in development, with guided exercise, shared monitoring and clinician review as intended capabilities.

Current status: in development, supported by HMRI through the ARC Connected Sensors for Health hub, with contributions from FASTlab researcher Jon Drummond. The project is exploring how evidence can help clinicians, carers and survivors understand progress and know when support may be needed.

Community · Good Design Award

Night Time Spaces

Challenge: anti-social behaviour in public spaces addressed through enforcement, not evidence. Communities had no voice in what worked or why.

FASTlab approach: co-design with community to identify pain points, generate evidence of what changed behaviour, commission artists to respond to that evidence in the public realm.

Result: Good Design Award winner. A replicable evidence-led model for public space activation that is now documented in The Elephant's Leg II.

Education · Net Zero · Government

Net:Zed — Net Zero Education

Challenge: net zero education programmes delivered to students without evidence of what changed in their understanding, agency or career intent.

FASTlab approach: developing the Project JANUS™ evidence and measurement approach for student cohorts in regional NSW schools, working with MCB Business Partners. This work informs the wider Evidence Intelligence Architecture.

Current focus: developing and testing an evidence measurement approach for net zero education, with potential for use across RIEP programs.

Stakeholder co-design · FASTlab space, Newcastle

Healthy@Home · RAPID Lego Serious Play workshop

Lego Serious Play · collaborative problem-solving

Singleton Living Laneways · night activation

Music and robotics · experimental creative practice

FASTlab space · research and co-design

Why trust FASTlab

Research rigour. Design practice.
Governed evidence systems.

FASTlab does not replace judgement. It makes the reasoning that informs judgement more visible, contestable and proportionate.

Documented projects

20+

Years combined research translation

Domains: health, energy, education, community, creative practice

Good Design Award

Research governance

NSW Department of Education SERAP process progressed · University of Newcastle ethics application submitted and under review · Avondale University research affiliation · Research participation in the ARC Connected Sensors for Health hub

Design principles

Explainability and audit as design principles — not afterthoughts. Human judgement preserved at every decision point. Evidence provenance maintained throughout.

Mario Minichiello · Co-founder · Visual journalist · Illustrator

Mario Minichiello spent thirty years drawing what he observed. FASTlab was built on the same principle — look carefully, interpret honestly, show what you found.

Why now

AI has made it easier to
generate answers. It has not made
those answers trustworthy.

As organisations adopt AI, they face a new problem: systems that generate confident-sounding outputs from opaque reasoning, with no audit trail, no provenance, and no way to explain the decision to a regulator, funder or affected community.

FASTlab builds the missing trust layer — governed evidence architecture that preserves provenance, calibrates confidence, maintains human review and produces decisions that can be defended.

Understand what is working

Identify where evidence supports positive outcomes and where further testing is needed.

Understand what is not working

Identify where evidence is too weak to justify continued investment without further review.

Scale with stronger evidence and clearer confidence

Build a stronger evidence base before committing to expansion.

The founders

Built by people who have spent
their careers at the intersection.

Co-founder & Director

Prof Paul Egglestone FRSA

Nearly two decades as a television producer — then research, innovation and evidence intelligence. FASTlab Director since founding. Professor of Creative Practice, Avondale University · Visiting Professor, Loughborough University.

Email → LinkedIn →

Co-founder

Prof Mario Minichiello PhD

Award-winning illustrator, visual journalist and designer. Thirty years of practice at the intersection of observation, interpretation and meaning. Professor of Design at Loughborough University, Birmingham City University and the University of Newcastle (NSW).

LinkedIn → Full bios + selected work →