Decision Engines
Four production decision engines. One operating standard.
Fable builds and operates decision engines that turn commercial, financial, and operational pressure into governed EBITDA, margin, and cash outcomes — embedded inside live workflows with one owner, one metric, and one cadence.
Engines operate inside live workflows. Outputs are thresholds, allocations, and governed actions — not recommendations delivered beside the workflow.
Baselines reconciled to finance truth. Assumptions explicit, haircut, and defensible before any outcome range is surfaced.
Audit trails, exception handling, and decision rights specified before deployment. Read-only validation precedes any write-back.
Revenue domain
Revenue Engine
Pricing, discount, and renewal guardrails that protect margin without stalling commercial flow.
Decision problem
Set price corridors, exception routes, and segment actions using demand, cost, and capacity signals.
Operating context
Commercial leaders balance price, demand, and margin under pressure. The Revenue Engine models elasticity, win rates, and capacity to protect margin and revenue quality.
Buyer focus
For CFOs and revenue leaders who need predictable margin lift and disciplined discounting.
Inputs
- Current price
- Unit cost
- Baseline demand
- Price elasticity
- Capacity limit
Levers
Outputs
- Recommended price
- Expected demand and revenue
- Gross margin and contribution margin
- Net EBITDA and margin impact
Operations domain
Efficiency Engine
Inventory, service, and capacity decisions that release cash without damaging delivery performance.
Decision problem
Set reorder points, buffers, and routing priorities under demand volatility and supply constraints.
Operating context
Service volatility and excess inventory persist. The Efficiency Engine turns demand uncertainty, lead time, and supplier performance into working capital and cost outcomes.
Buyer focus
For COOs and operations leaders who need working capital release and service stability.
Inputs
- Demand history by product class
- Lead time by supplier
- Service level targets
- Supplier reliability
Levers
Outputs
- Reorder point and safety stock
- Fill rate and backorder volume
- Working capital tied up and released
- Net EBITDA impact
Capital domain
Strategic Engine
Capital allocation and sequencing decisions with downside protection and hurdle-rate discipline.
Decision problem
Compare scenarios, sequencing options, and resource commitments under capital constraints.
Operating context
Capital allocation decisions face uncertainty and limited scenario coverage. The Strategic Engine simulates outcomes, downside risk, and hurdle rate attainment.
Buyer focus
For Private Equity operating partners and CFOs who need capital allocation confidence.
Inputs
- Portfolio capital
- Allocation mix
- Expected returns
- Volatility assumptions
- Time horizon
- Hurdle rate
Levers
Outputs
- Expected value and percentile range
- Value at risk and drawdown
- Probability of loss
- Hurdle rate attainment
Reliability domain
Reliability Engine
Monitoring, drift control, and release discipline that protect decision quality in production.
Decision problem
Detect drift, restore performance, and protect value before degradation reaches operators or finance.
Operating context
Decision systems drift, data quality degrades, and monitoring is inconsistent. The Reliability Engine stabilizes performance and protects value at risk before degradation reaches the operating team.
Buyer focus
For CTOs, data leaders, and risk owners who need reliable decision systems in production.
Inputs
- Baseline accuracy
- Drift rate per month
- Monitoring frequency
- Retraining cadence
- Decision volume
Levers
Outputs
- Monthly value at risk
- Time to detect and recover
- Reliability score
- Value protected
Delivery model
From private demo to governed production in four stages.
Each stage ends with a clear go-forward decision before the next commitment is made. The QOA confirms whether the opportunity is real, measurable, and worth deployment.
Quantified upside, feasibility map, and implementation-ready engine specification for one decision workflow.
Contained prototype deployed against real data to prove the operating hypothesis in live workflow.
Production integration, monitoring, and governed operating cadence inside existing systems.
Monitored operation with drift controls, cadence reviews, and measured performance against the baseline.
Start with one workflow. One owner. One decision worth making.
The private demo and QOA exist to confirm whether the opportunity is real, measurable, and worth deployment — before any broader commitment is made.