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How we work

Better decisions are built, not bought.

Every organisation produces data. Few turn it into intelligence. We close that gap one layer at a time, starting from the decision, not the technology, and we stay until better decisions are how the business works.

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Fig. 1 — The intelligence pyramidSection A–A
  1. Intelligence05 What should we do?
  2. Insights04 Why, and what comes next?
  3. Knowledge03 How does it all connect?
  4. Information02 What is happening?
  5. Data01 What do we hold?
  6. Open by designUnder every layer
[01] How we work

Start small, pay as you grow.

  1. 01Pick the decision

    Pricing, forecasting, where to invest next: one call that matters.

  2. 02Build the layers it needs

    Only the data, knowledge and models that decision needs, on the cloud you choose.

  3. 03Prove it

    We judge the work by the decision made differently, and its result.

  4. 04Scale, then hand over

    Grow as results prove the value. We stay until it works; you keep everything.

No upfront infrastructure costs. Start small, pay as you grow.

[02] What we build

From data to intelligence, one layer at a time.

Start with one decision that matters, and scale as the results prove the value.

  1. 05 · Smarter decisionsIntelligenceWhat should we do?AI recommends from your own data; your people decide.
  2. 04 · AI and machine learningInsightsWhy, and what comes next?Models find patterns, risks and forecasts.
  3. 03 · Knowledge graph and ontologyKnowledgeHow does it all connect?Every fact linked, defined and sourced.
  4. 02 · Digital transformationInformationWhat is happening?Connected systems give one trusted view.
  5. 01 · Cloud-native platformDataWhat do we hold?Captured at cloud scale, paid for as used.
[03] Grounded intelligence

AI that shows its working.

We connect your data into a knowledge graph, a connected model of your organisation, so AI answers from your own facts and shows where each one came from.

  1. STEP 01A question

    “Which customers are we most likely to lose this quarter, and why?”

  2. STEP 02What the words mean

    The ontology fixes what “customer”, “lose” and “quarter” mean in your business.

  3. STEP 03The connected facts

    The knowledge graph links every fact to each customer, with its source and date.

  4. STEP 04Agreed measures

    Models score each risk; churn is calculated the one agreed way.

  5. STEP 05An answer, with sources

    The customers, the reasons, and the records behind each one.

  6. STEP 06Your people decide

    The decision and its result go back into the graph.

16%54%

In one benchmark, GPT-4 answered 16% of 43 enterprise questions correctly when it queried a SQL database directly, and 54% when the same data was described by a knowledge graph. One insurance data model; not a promise. Sequeda, Allemang and Jacob, 2023

When the graph holds no evidence, the answer says so.

[04] The foundation

Open by design.

Everything we build runs on open standards and belongs to you, so your data, your model of the business and your code move with you.

  • Open standards

    Knowledge modelled in W3C standards such as RDF and OWL; data in open table formats such as Apache Iceberg.

    CHECK → every design names its standards
  • Open source where it fits

    Well-supported open-source software where it does the job; commercial products where they do it better.

    CHECK → each component, its licence and why
  • Vendor-neutral

    AWS, Azure or Google Cloud; Databricks, Snowflake, Fabric or open-source stacks, chosen by fit.

    CHECK → a written rationale; partners declared
  • Yours to keep

    You own the code, the ontology, the data and the documentation.

    CHECK → an ownership clause and an exit pack

Start with one decision that matters.

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