Discovery Agent

Scope the Pilot Before You Sign the Programme.

The Discovery Agent is the pre-sales workflow for mapping source systems, metadata, and business signals into an evidence-led pilot plan. No raw operational data has to leave your environment.

Five Steps. A Clear Pilot Map.

1

Connect

2 minutes

Point the Discovery Agent at your existing database or CRM. Read-only access. Nothing is copied or moved.

2

Scan

3 minutes

The agent scans metadata — table schemas, field distributions, relationship graphs. It never reads raw record values.

3

Map

2 minutes

Semantic attributes are automatically suggested: churnRisk, conversionProbability, engagementLevel, and more.

4

Score

2 minutes

Context facts are generated with confidence scores and provenance chains. You see exactly which source fields drive each insight.

5

Report

1 minute

A full ROI report shows projected lift: conversion improvement, churn reduction, and revenue impact over 90 days.

Synthetic Industry Time Machine

Synthetic agents help frame what a pilot should test across six industries. They are planning aids, not customer performance claims.

Car Dealer

Predict which leads will convert, which stock will sell, and which customers will return for servicing.

Manufacturer

Forecast demand, optimise supply chain context, and identify quality risk patterns before they become recalls.

E-commerce

Personalise product recommendations, predict cart abandonment, and attribute conversions to specific context signals.

Professional Services

Score proposal win probability, identify cross-sell opportunities, and predict project overruns.

Retail

Optimise store layouts, predict footfall, and personalise loyalty programmes with real purchase context.

Healthcare Logistics

Predict supply shortages, optimise delivery routes, and ensure compliance with NHS and regulatory requirements.

Live Intelligence

What the Discovery Agent Finds

Illustrative signals the discovery workflow can look for once access, consent, and source-system scope are agreed.

Context scenario
Automotive

Parts Manufacturer — 12 plants, SAP + IoT

£180k downtime avoided

Pump 47-B in Stuttgart shows rising inlet pressure variance for 5 consecutive days — exact signature seen before Pump 32-A failed. Last bearing replacement was 11 months ago. Recommended: schedule maintenance within 14 days. Projected saving: £180k in avoided downtime.
Context scenario
Consultancy

Management Consultancy — 120 consultants, Dynamics 365

£1.2M untapped pipeline

Practice area ‘Supply Chain Transformation’ has a 62% proposal win rate versus 28% firm average — but only 4 of 120 consultants are tagged with this capability, at 94% utilisation. Recommended: upskill 6 from ‘Operations’ practice. Projected revenue: £1.2M in addressable pipeline currently being declined.
Context scenario
Grocery

Grocery Chain — 48 stores, weather + loyalty integration

£28k revenue captured

Rain forecast for Saturday across the Liverpool City Region. Historical pattern: rainy Saturdays increase online delivery orders by 38% but reduce in-store footfall by 22%. Recommended: pre-staff 4 additional delivery drivers and reduce bakery production by 15%. Projected impact: capture £28k in delivery revenue.
Context scenario
Healthcare

Private Hospital Group — 4 hospitals, 22 theatres

£1.8M revenue opportunity

Theatre utilisation across the group is 71% — target is 85%. Three root causes: 14% of slots blocked by late consultant cancellations, pre-auth delays averaging 4.2 days from insurer Vitality, and MRI scanner downtime in Hospital 2. Projected impact: increase utilisation to 82%, generating £1.8M additional revenue/year.
Context scenario
Food Manufacturing

FMCG Manufacturer — 6 production lines, Dynamics 365

£400k recall prevented

Customer complaint rate for SKU ‘Premium Lasagne 400g’ rose 340% in 14 days. All complaints trace to batches produced on Line 4 between May 3-7. Line 4 oven zone 3 temperature was 8°C below setpoint — heating element degrading. Recommended: immediate quality hold on remaining 4,200 units. Prevent £400k+ recall.
Context scenario
Higher Education

Research University — 28,000 students, on-prem metadata only

18% attrition reduction

International student cohort from Region Y shows 41% higher dropout risk if they don’t engage with the careers service in first 8 weeks. Cross-referenced with attendance and library usage data. Recommended: trigger proactive outreach in Week 6. Projected impact: 18% reduction in international attrition.

Pruning Accuracy

The Discovery Agent is designed to separate durable context signals from noise, then mark what must be validated during the pilot.

Source-system map72%
Metadata coverage85%
Pilot signal definition93%
Governance review97%

Ten Minutes to Clarity

No raw data movement. A scoped pilot plan. Evidence before expansion.