Know what is likely to happen. Decide what to do about it.

Fable builds predictive Decision Engines for UK and US upper-mid-market and enterprise operators—combining production ML, cross-system mapping and financial attribution.

EvidenceERP, CRM and operating records joined at the cutoffForecastOutcome, timing and uncertainty estimated before actionDecisionNamed action, owner, deadline and expected effect

A forecast is useful only if it changes a decision.

Each engine handles one recurring operating choice. Models estimate the uncertain outcomes. Rules exclude unsafe or impossible actions. Optimisation decides where limited time or capacity should go.

  1. 01
    Reconstruct the position

    Join the records that describe the same project, product, customer or obligation at the decision cutoff.

  2. 02
    Forecast the outcome

    Estimate what is likely to happen, when it may happen and how uncertain the forecast is.

  3. 03
    Compare available actions

    Remove options that breach authority, policy, capacity or operating constraints.

  4. 04
    Choose the work

    Rank the remaining actions by their expected operational and financial effect.

  5. 05
    Measure the result

    Record what was approved, completed and achieved, then feed the outcome back into the engine.

Project Margin RescueReference run
Evidence spineStatusCutoff
ERP · project accountingAuthoritative08:42
PSA · time and deliveryReconciled08:38
Billing · WIP and ARCurrent08:40
Predicted outcomeMargin-at-completion distribution
Protected floor
DownsideForecast rangeUpside
01
Feasible interventionSubmit bounded EAC revision

Northbank Programme · owner PMO South · due 14:00

Expected effectProtect marginuncertainty shown in workbench

Three systems in one decision mechanism.

Production ML estimates the uncertain future. Cross-system operational mapping establishes the facts at the decision cutoff. Financial attribution keeps predicted value, realised value and finance recognition separate.

01

Cross-system mapping

Match identities, dates, units and authority across the systems involved in the decision.

02

Production machine learning

Estimate the possible outcomes, their timing and the uncertainty around them.

03

Financial attribution

Keep predicted risk separate from action effect, then compare the result with the original expectation.

Decision Engines for the work that moves financial performance.

Fable applies the same decision discipline across commercial economics, revenue, cash, supply, workforce, operations, procurement, capital and risk. Explore two engines in detail below, or find the decision that matches your operation.

Project Margin Rescue Engine

Determine which active project requires intervention now to protect margin, cash timing or delivery economics.

Primary operator
Finance, PMO and delivery leadership
Cadence
Weekly, with month-end escalation
Explore Project Margin Rescue
Project intervention portfolioWeekly decision cut
Evidence5 systemsDecision grainProject × cutoffBoundaryApproval required
Harbour EastEAC driftSubmit forecast revisionDecision now
Lumen DeliveryBilling lagIssue eligible invoiceApproval
Alder ControlsCost exposureCorrect supplier itemMonitor

Range-to-Cash Trading Yield Engine

Choose the product, customer and branch actions that improve cash, contribution and service together.

Primary operator
Trading, category, finance and supply
Cadence
Weekly and event-driven
Explore Range-to-Cash
Range action portfolioWeekly decision cut
Evidence6 systemsDecision grainSKU × branchBoundaryApproval required
Alder Chilled · CentralExcess coverSuspend replenishmentDecision now
Juniper Pantry · NorthService exposureTransfer 48 unitsApproval
Elm Bakery · SouthWeak yieldHold through reviewMonitor
Explore Decision Engines

Inspect how the recommendation was produced.

The engine retains the source records, model version, constraints, alternatives, selected action and subsequent outcome for every decision.

See what can be inspected
01Production code executes the reference decision
02Models are compared against fixed baselines
03Every action has an owner and completion test
04Expected and realised value remain separate

Start with one decision. Prove it before deploying it.

The Qualification of Opportunity Assessment checks whether the decision is valuable, the historical record can support it and the operator can act on the result. Only then does the work move to a pilot.

01

Paid QOA

Test the decision, available history, authority to act and value at stake.

02

Pilot

Run the engine against an agreed baseline using the client’s operating record.

03

Production

Deploy the approved models, workflow, integrations and fallback.

04

Stewardship

Monitor performance, retrain when evidence warrants it and account for results.

Product-grade software for the operating systems around the decision.

The Fable Systems Library provides reusable foundations for CRM, scheduling, finance, accounting, quoting, billing, workflow, portals and integration. Bespoke Builds adapt that IP to the way the business actually runs.

  • Production software, not a workshop or management playbook
  • Built around the client's data model, workflow and commercial edge
  • A durable substrate for future Decision Engines where useful
Explore the Systems Library
Fable Systems LibraryReusable product foundations
01CRM & portals
02Finance & billing
03Scheduling & workflow
04Integration platforms
Human approvalAuthority and permitted actions are explicit.
Tenant isolationClient records stay inside the approved boundary.
Deployment choiceCloud, private cloud or client-controlled infrastructure.

Bring us one recurring decision with a measurable financial consequence.

Tell us who makes it, how often, which systems hold the evidence and what a better decision would change.

Discuss the decision