1. Data Strategy & Audit

Purpose: To establish a clear picture of current data assets.

We help map data inventories, identifying where critical information resides across spreadsheets, legacy systems, and modern SaaS platforms. This process helps clarify ownership and highlights quality gaps.

  • Questions to investigate: Where does this metric originate? Who is responsible for its accuracy?
  • Planning outputs: Source mapping documentation, quality assessments, prioritised next steps.
  • Limitations: An audit provides visibility; it does not automatically fix underlying legacy software flaws.
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2. Business Intelligence

Purpose: To translate raw data into structured, reviewable formats.

Effective reporting requires agreement on KPI definitions and reporting cadences. We support dashboard planning to ensure audiences receive the operational or management views they require.

  • Questions to investigate: What decisions will this dashboard drive? How frequently is the source data refreshed?
  • Planning outputs: KPI definition libraries, architecture planning, audience requirement matrices.
  • Limitations: Dashboards only reflect the data provided; they require sustained management review to remain valuable.
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3. AI Readiness

Purpose: To evaluate the foundations required for careful AI adoption.

We work with teams to map potential use cases against current data realities. This involves assessing structural readiness, privacy considerations, and planning for necessary human oversight.

  • Questions to investigate: Is the underlying information structured and accurate? How will outputs be verified?
  • Planning outputs: Use-case scoring, pilot scope documentation, risk evaluation summaries.
  • Limitations: We do not guarantee ROI or 100% accurate AI outputs. Human review remains essential.
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4. Automation Planning

Purpose: To map processes for potential efficiency gains.

Reviewing manual, repetitive reporting tasks to determine if they can be safely consolidated or scheduled, while ensuring exception handling is documented.

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5. Data Governance

Purpose: To establish rules for data management.

Defining permissions, access controls, and retention considerations to help maintain an orderly information environment.

6. LLM / RAG Planning

Purpose: Preparing internal knowledge for retrieval systems.

Retrieval-Augmented Generation (RAG) relies entirely on the quality of internal documents. We assist in planning document structure, permissions, and source-checking workflows before deployment.