Scope a 6-week pilot
Scope a 6-week pilot
The trust layer beneath AI

Turn scattered organisational knowledge into source‑linked AI answers.

For the executive on the hook for a number they must defend — answers they can trace to the source, not a confident guess.

Amidflow builds the semantic intelligence layer between your documents, data, dashboards, metrics and AI agents — giving copilots the context, provenance and meaning they need to support real decisions.

Scope a 6-week pilot See how the pilot works

Founder-led by senior data, BI, analytics, governance and decision-intelligence experience across enterprise reporting and high-volume data environments.

01 — Who this is for

You answer for the board figure, the reporting cycle, the AI the business acts on — in public.

02 — The Problem

Copilots fail when business knowledge is not structured.

Organisations are racing to put AI copilots and agents to work — straight on top of scattered information. Business knowledge lives across PDFs, policies, dashboards, spreadsheets, systems, reports, emails, decks and people. Without a semantic layer, AI can't reliably tell what matters, where it came from, who owns it or whether it can be trusted.

  1. 01

    The answer exists, but nobody knows where

    Knowledge is trapped across documents, dashboards, systems and people.

  2. 02

    The AI sounds confident, but cannot show its work

    Outputs lack source links, definitions, business context and ownership.

  3. 03

    The same metric means different things across teams

    KPIs, terms and entities are not governed.

  4. 04

    Every new question restarts the analysis

    Logic is rebuilt manually instead of structured once and reused.

Today

Documents · dashboards · spreadsheets · systems · people AI guesses

With a semantic layer

The same sources, structured an answer you can trace

03 — The Missing Layer

The semantic layer between knowledge and AI.

Amidflow structures the business meaning trapped inside your information — what each thing means, how it connects, and where it came from — into a semantic intelligence layer that AI agents can reason over with evidence, not guesswork.

Scattered knowledge

Docs Dashboards Databases Spreadsheets Reports Policies Email
The semantic layer Governed graph
Client Contract Supplier Project Deliverable Risk Document Meeting Dataset Dashboard KPI Decision Initiative
Governed by Owner Lineage Trust Access

AI & decision workflows

Source-linked answers Decision copilots Executive reporting Research workflows Risk signals

04 — The Product

A governed graph of what your organisation knows.

The Semantic Intelligence Layer connects your organisational knowledge into a reusable structure that AI agents, dashboards and decision workflows can use. It doesn't replace your data warehouse, BI tools or document systems — it adds the missing layer of meaning between them.

  • Business entities
  • Relationships
  • Metrics & definitions
  • Source links & evidence
  • Ownership & governance
  • Retrieval workflows
  • AI answer evaluation
  • Decision context

05 — The Payoff

Ask the business a question.
Trust the answer — and actually use it.

Once information is governed, AI stops serving the confident guess. Every answer comes with its receipts — owned, defined, traceable sources — so leaders can ask in plain language, see the evidence behind what comes back, and stand behind the number when the room asks.

The difference between an AI demo and an AI you can run the business on is two words: sourced — and adopted.

Illustrative

Why did gross margin fall last quarter?

Gross margin fell 1.9 points, driven mainly by promotional pricing in the South region1 and higher inbound freight2. Volume held — the movement is price- and cost-led, not demand-led3.

Sources
  • 1 Q3 board pack
  • 2 Logistics ledger
  • 3 Pricing model
Source-linked Governed Owner · Finance

Receipts, not a confident guess.

06 — The Pilot

Start with one corpus, one workflow and one success test.

Scattered knowledge today → a source-linked answer in 6 weeks. Measured, not asserted.

The first engagement is not a transformation programme. It's a contained pilot that proves whether a semantic intelligence layer can improve one real workflow in 6 weeks.

  • Fixed scope
  • Fixed price
  • Defined success test
  • Clear handover
  • Optional extension roadmap
Scope a 6-week pilot

The 6-week method

  1. 01
    ScopeWeek 1

    Select the corpus, workflow, sponsor and success test.

  2. 02
    StructureWeeks 2–3

    Map sources, entities, metrics, definitions and relationships.

  3. 03
    BuildWeeks 4–5

    Build the graph prototype and source-linked retrieval workflow.

  4. 04
    EvaluateWeek 6

    Test answers, measure quality and recommend stop, extend or scale.

A pilot fits when

  • A leadership workflow depends on fragmented data, documents or reports.
  • There is a measurable before / after — time saved, manual steps removed, retrieval improved.
  • A decision owner can sponsor the work.
  • The goal is to prove value in one contained area before scaling.

Not yet, if

  • The aim is open-ended AI experimentation with no real business workflow.
  • There is no owner for the decision or the information asset.
  • The expectation is broad transformation rather than one measurable proof.

07 — Use Cases

Where the layer creates value first.

  1. 01

    AI Copilot Readiness

    Problem

    Your organisation wants copilots or AI agents, but the underlying knowledge is scattered and ungoverned.

    Amidflow builds

    A semantic layer of entities, definitions, source links, permissions and decision context.

    Outcome

    AI answers become more useful, traceable and trusted.

  2. 02

    Document Intelligence

    Problem

    Policies, reports, contracts, decks, research and emails hold valuable knowledge but are hard to search, compare and reuse.

    Amidflow builds

    A structured knowledge graph that maps documents to entities, topics, decisions, risks and sources.

    Outcome

    Teams retrieve the right answer and evidence faster.

  3. 03

    KPI & Reporting Trust

    Problem

    Teams disagree on numbers, definitions and reporting logic.

    Amidflow builds

    A governed metric layer connecting KPIs to definitions, source systems, owners and lineage.

    Outcome

    Board reporting becomes more defensible and less manual.

The same layer also powers:

Consulting & Advisory Intelligence

Reusable project knowledge, client material, research, proposals and insight libraries — so prior work compounds instead of being rebuilt.

Investment & Research Intelligence

Source-linked workflows across filings, transcripts, notes, research and market signals — evidence behind every memo.

08 — Why Amidflow

Built for the gap between data systems and real decisions.

Amidflow combines data strategy, business intelligence, governance, analytics engineering, semantic modelling and behavioural decision design. The result isn't another AI interface. It's the structured knowledge layer required to make AI useful in real organisational decisions.

Engineering excellence makes a number traceable; business execution makes it trusted — and few teams are built for both.

And adoption is engineered, not hoped for: every answer carries visible provenance and a named owner, framed in the language the decision is made in and surfaced where the decision happens. We build the system people trust — not a programme that trains people to trust the system.

Amidflow is founder-led, with practical experience building enterprise BI, analytics, data governance and reporting capabilities across complex, high-volume operating environments.

  • 250+ retail sites · Azure Databricks · Maxol We build and govern the layer at real scale.
  • MSc Behavioural Economics · UCD We design answers leaders actually trust and adopt.
  • Commercial strategy · Stax We start from the executive's question, not the tooling.
01

Source-linked or it doesn't ship

Every accepted answer must trace back to evidence.

02

Govern before you generate

Definitions, ownership and controls come before AI features.

03

Start contained

One corpus, one workflow and one success test before scale.

04

Handover matters

Clients should not be trapped in a black box.

09 — The Alternatives

Every path gives you something. The difference is what each leaves with you.

The question isn't whether to act — it's which option leaves you, personally, still holding the number. An honest look at what each one gives, and what it leaves with you.

  1. Do nothing GivesA confident guess. Leaves youDefending the number on memory.
  2. Your internal BI team GivesA backlog. Leaves youYour number, eventually — behind everything else.
  3. A big-firm programme GivesA 12–18 month transformation. Leaves youThe risk you carry while it runs.
  4. A copilot GivesA fluent answer. Leaves youNo citation, no owner, no adoption.
  5. A strategy house GivesA decision frame. Leaves youNo governed layer underneath it.
  6. GivesOne number, defensible in one pilot — governed and adopted, senior-only. Leaves youThe proof carries the risk — not you.

10 — Start

Have an AI use case blocked by scattered knowledge?

Start with a focused scoping conversation. We'll find one number — or one decision — you need to stand behind, and prove a semantic intelligence layer can make the answer defensible.

Scope a 6-week pilot

30 minutes. No deck required.

A number you can't defend → one you can, in one pilot.

  • Success test agreed up front — measured before / after (e.g. retrieval time, reporting disputes, traceability).
  • Fixed scope and price. You keep the deliverables either way.
  • An honest stop if it isn't worth it.

You don't have to trust us — only the measured result. No wall of logos.