Good Enough Consulting

An algorithm is math on a blackboard—until you make it think.

We design the living brain of structured intelligence systems (AI).

A structured intelligence system is more than code—it’s people and algorithms interoperating.
We specialise in optimising the intelligence of that process.

At the Good Enough Lab, we build data systems that don’t just scale—they think.
System thinking is a living process: as people evolve their questions, systems must evolve with them.
Design can’t be perfected upfront—it must be structured to adapt in a way that’s observable and trustworthy for humans.

Our consulting services move organisations from chaos to coherence.
We bring opinionated inclusivity, test-driven development, and grounded migration strategies—shaped by over a decade of experience engineering machine-learning pipelines in research, start-ups, scale-ups, and enterprise environments.

We’re not here to optimise your dashboards.
We’re here to help you build a system of analytical inquiry you can trust.

→\to Learn more about good enough methodology research

Data Architecture Strategy for Migration & Inclusive Automation

It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.

Most data migrations fail because they forget the humans.
We design structured intelligence systems that reflect real workflows—not just schemas.

Robust systems maintain clear boundaries between source, semantic, and analytic layers.
When these layers are collapsed, data reuse becomes brittle and unsustainable.

It’s costly to rewrite pipelines for every analysis.
It’s better to build a living architecture of semantically meaningful tables that grow with the organisation—
flexible enough to recombine, stable enough to trust.

pipeline raw Ingestion Layer Ensures data freshness and source integrity source Source Layer Converts to source-aligned data entities raw->source semantic Semantic Layer Integrates data entities across sources source->semantic analytic Analytic Layer Enriches data entities for specific analyses semantic->analytic deploy Deployment Layer Validated analyses and data exports that preserve lineage analytic->deploy

Our Structured Intelligence Governance starter kit, tailored to your stack, includes:

  • Test-driven data migration plan (the Lab uses JIRA inhouse, and have experience with ClickUp and Monday)
  • FAIR data entity modelling (we favour DBT, git-based, cloud-native approaches)
  • Embedded validation and observability
  • ESG-aligned governance scaffolds

→\to More on ESG

We make your system smarter—without making your people invisible.


exposures:
  - name: Analysis
    owner [TODO LOOK THIS UP]: Someone overburdened
    description: Needed by [these people] to do [some analyses]...
    I forget what goes here:
      - this_analytic_entity
      - that_analytic_entity 


sources: 
  - name: this_source
    description: We need this for this_entity analyses...
    data_tests:
      - unique
        config:
          columns: "source_unique_a || source_unique_b"
      - not_null
        config:
          columns: "source_unique_a || source_unique_b"
      - freshness:
        config:
          ... I forget, honestly, will look up


models: 
  - name: this_source_entity
    description: We understand this model in 
      terms of these columns...
    columns:
      - name: entity_id
        data_tests:
          - unique
          - not_null
      - name: source_id
        data_tests:
          - not_null
  - name: this_data_entity
    description: This data entity comprises a 
      summary of this_entity sources, 
      where each row may thought of as....
    columns:
      - name: entity_id
        data_tests:
          - unique
          - not_null
      - name: source_id
        data_tests:
          - not_null
  - name: this_analytic_entity
    description: This analytical model provides 
    observations associated with this_data_entity, 
    enriched with attributes from another_entity. 
    It is in production to....
    columns: 
      - name: this_data_entity
        description: This data entity comprises a 
          summary of this_entity sources, 
          enriched with that_entity attributes, 
          where each row may thought of as....
        data_tests:
          - unique
          - not_null
      - name: source_id
        data_tests:
          - not_null

Change Management through FAIR Audits

You don’t need another compliance checklist.
You need to know whether your system is FAIR to the people inside it.

We conduct in-depth audits—person by person, role by role—to uncover how data practices actually function.
We map epistemic flows, surface systemic blockers, and design transitions that earn trust.

  • FAIR workflow audit
  • Sociotechnical validation plan
  • Governance recommendations grounded in lived experience

This is change management that builds trust before transformation.

Speaking & Advisory

Structured intelligence isn’t just a technical upgrade.
It’s a shift in how we understand machines, data, and each other.

We offer:

  • Keynotes on the brain of structured intelligence systems (AI)
  • Executive briefings on test-driven governance and epistemic resilience

Your intelligence system has a nervous system.
We help you wire it wisely.