A shared knowledge model
Agreed entities, identifiers and definitions for your domain: products, requirements, contracts, processes, assets or organisations. The same concept has a consistent meaning across sources.
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IRONBAY DATA / 02
Connected knowledge
Give information meaning. Give your systems context.
Connect records, documents and business relationships into knowledge your teams can navigate and your AI can use. Make it easier to understand what a fact means, how it relates to the question and which evidence supports it.
01 / TANGIBLE DELIVERABLES
What you receive.
An explicit model of the things that matter to your business, the relationships between them and the evidence behind them. Built around the questions your teams and systems need to answer.
HOW IT WORKS
From individual facts to an answer with evidence.
Define the records, documents and questions in your domain.
Customer requirement
Product record
Supporting document
Link relevant facts with explicit meanings and source references.
A traceable evidence path
R-18Requirement
met by stated specification
P-42Product
supported by document
TR-09Evidence
Make each connection inspectable by people and usable in AI retrieval.
FOR YOUR TEAMS
Connection view + source evidenceFOR YOUR AI
Entities + relationships + referencesRelationships with evidence
A set of defined links between records and documents, with supporting references and relevant dates. A documented relationship remains distinguishable from a proposed match or an inference.
A view people can explore
A report showing related records, connection paths and source evidence around the use case. Business teams can inspect how information fits together and identify what still needs review.
Context for AI retrieval
Structured entities, relationships and document references for your knowledge and retrieval workflow. Graph, vector and RAG integrations are designed around your environment and agreed access rules.
02 / FROM BRIEF TO USE
From a customer requirement to the evidence behind a recommendation.
- The brief
- A technical sales team needs to understand which component meets a pressure requirement and where that claim is documented. Its AI assistant needs the relationship, not just similar-looking text.
- The delivery
- A linked set of requirements, product records and supporting test documents. Each connection states its meaning, source and review status. A report lets the team follow the path from question to evidence.
- In the workflow
- A sales engineer reviews a proposed component and its supporting document. An AI assistant can retrieve that same path to draft an explanation, with source references for the engineer to check.
DELIVERABLE PREVIEWIB / 01
A PATH TO THE EVIDENCE
- REQUIREMENT / R-18Operating pressure: 40 barmet by stated specification
- PRODUCT / P-42Industrial valvesupported by document
- EVIDENCE / TR-09Test report · page 4
One supported requirement. Overall suitability needs specialist review.
03 / ACROSS YOUR BUSINESS
For the teams making decisions. And the systems behind them.
The brief determines the product. These examples show how the same approach supports different teams and the AI tools they work with.
Executive & strategy
See the dependencies behind a decision.
Receive a map linking initiatives, assets, suppliers, owners and supporting documents. Leadership can inspect dependencies, while an AI briefing assistant retrieves the relevant connections for a decision memo.
Finance & risk
Trace a figure back to its meaning.
Receive defined links between metrics, business units, reporting periods, contracts and source records. Finance can review scope and assumptions; AI assistants can retrieve the right definition and evidence alongside a figure.
Sales & account teams
Find a credible route to an opportunity.
Receive evidence-linked account, partner and supplier relationships alongside similarities in business needs. Sales can examine possible introductions, and AI account planners can prepare context-rich briefs for review.
Marketing & product
Connect customer needs with relevant evidence.
Receive a structured view of themes, customer requirements, product capabilities and approved supporting material. Marketing can find the right proof points; AI tools can retrieve context for segment-specific content drafts.
For your people
Connection views and source references make complex information easier to discuss, challenge and use. A team can follow the relationship behind an answer instead of relying on an unexplained score.
For your AI systems
Vectors help retrieve relevant material; graphs retain explicit relationships; RAG brings selected evidence into a model’s input. We scope the knowledge and integrations needed for your questions, including Neo4j where appropriate.
04 / A FOCUSED FIRST ENGAGEMENT
Start with the questions your current systems struggle to connect.
- 01
Choose a set of real questions and the sources behind them.
- 02
Define the entities, relationship meanings and evidence requirements.
- 03
Review the connected output before expanding coverage or integration.
PRACTICAL QUESTIONS
Before we begin.
Do we need to replace our existing systems?
The starting point is the knowledge your workflow needs. We can prepare a defined set of entities, relationships and source references from agreed systems. Integration into your existing infrastructure is scoped separately around access and delivery requirements.
Does a connection prove causation or commercial interest?
No. A relationship has a specific, documented meaning. A shared supplier, a similar requirement or an associated document does not by itself prove causation, buying intent or suitability. The output makes evidence and interpretation distinguishable.
Can we begin with a report before a graph integration?
Yes. A prepared report can validate the questions, relationship model and source coverage with your team. A graph or retrieval integration can follow once the knowledge is useful in practice.