The following use cases are an illustrative example per sector. Each snapshot shows what the agent evaluates before acting, what it executes autonomously when it can do so with guarantees, and what the analyst receives when it cannot.

Prescriptive Decision AI for Insurance
Insurance
Fast-track and claim triage

Triage models classify each incoming claim into auto-pay, request documents, or investigate. Without context, the adjuster does not know why a claim landed in "investigate" or which documents would move it to auto-pay — and the default response is full investigation, costing €380 per case for an outcome that, in 91% of low-risk profiles, is still payment. AyGLOO adds an agentic layer on top of that model: the agent evaluates model reliability for each specific claim, compares in real time the net cost of each possible action, and acts autonomously by choosing the one that minimises expected loss. For a portfolio of 10,000 claims/year, the difference between investigating by default and routing with criteria exceeds €1.1M/year in avoidable operating cost.

1
The agent auto-settles 67% of claims with no human intervention. The adjuster handles only edge cases where their judgement adds real value.→ 6,700 cases/year resolved with zero operating cost
2
ISA identifies the segment’s true risk profile; CF computes the minimal documentation that moves the claim to auto-pay; and what-if isolates which signal is blocking fast-track — together they eliminate unnecessary investigations.→ Cost per case: €45 docs vs €380 full investigation
3
Network analysis detects coordinated fraud rings across adjusters, repair shops, and linked insureds — invisible when analysing each claim in isolation.→ Organised fraud detected before payment, not after
4
The economic decision function compares in real time the net cost of auto-settle, request documents, or investigate — and the agent chooses the action that minimises expected loss, not just risk.→ From fixed thresholds to per-claim economic optimisation
Today: what an adjuster typically receives
Claim #CLM-20260215-0291 Triage: INVESTIGATE Home burglary · €4,100 · No additional context
With AyGLOO. Same claim, fully enriched
Claim #CLM-20260215-0291 · Home burglary €4,100 Tenure: 14 years · First claim The agent acts
XAI Why it was not auto-settled Twin Reliability-level rules ISA Segment risk profile CF Documents that trigger fast-track Econ Economic decision function Action Agent decision PDF Regulatory traceability
1. Why it was not auto-settled. Twin model (depth 7 · fidelity 95.7%)
100%IF police_report = false AND items_without_receipt ≥ 2 → Incomplete documentation: fast-track pending. The agent requests before paying or investigating.
82%IF claim_reported_11_days_late = true AND first_claim_in_14_years = true → Atypical but low-risk profile. Delay is unusual, but history supports legitimacy.
58%IF first_claim_in_14_years = true with no other factors → Weak signal in isolation. Do not escalate to investigation based on this alone.
The full-confidence rule triggers the agent action: request documents automatically, without waiting for the adjuster. 84% of similar profiles with complete documentation are paid via fast-track. Missing documents are the only barrier — not customer risk.
XAITwin
2. Segment risk profile (ISA)
Micro-segment: "tenure >10 years, first claim, residential" · Confirmed fraud rate: 1.2% · Payment probability after full investigation: 91% · Full investigation operating cost: €380 · No drift detected in the last 12 weeks · High reliability: act with confidence.
ISA is the agent’s double-check before acting: it confirms the model behaves well in this segment and provides the inputs for the economic decision function. If the light were amber, the agent would route to the adjuster even if the score looks clear.
ISA
3. CF. Minimal documents that trigger fast-track
Police report: triage moves from INVESTIGATE to FAST-TRACK automatically · Police report + receipts for items >€800: fast-track with 0.94 confidence · No documents within 7 days: escalate to full investigation as a last resort
CF removes operational ambiguity: the adjuster does not need to decide what to request. The agent generates the exact request and sends it automatically.
Counterfactual is not sensitivity: it is the concrete minimal action that resolves the case. Fully investigating this claim would mean paying €380 to obtain the same outcome that costs €45.
CF
4. Economic decision function. Expected net cost by action
Action
Operating cost
Residual risk
Total net cost
Auto-settle
€0
€49
€4,100 × fraud 1.2%
€49
Request docs ✓
€45
comms + handling
~€0
fraud eliminated if provided
€45
Full investigation
€380
adjuster + handling
~€0
€380
→ The agent chooses requesting documents: it eliminates fraud risk at the lowest net cost (€45 vs €49 vs €380) · Investigating would cost 8× more for the same outcome
The agent decision is not based on a fixed risk threshold: it compares expected loss of each action using ISA inputs (segment fraud rate, real operating cost, payment probability). This turns triage into an optimisable, auditable economic function — not a default “investigate” rule.
Econ
5. Agent decision
The agent acts — no adjuster intervention
Sends the document request automatically today: police report + receipts for items >€800 · Customer communication generated: "We are ready to process your claim. To complete the assessment we need: [1] police report reference number and [2] purchase receipts for items above €800. Once received, we will settle within 48 hours." · Upon receiving documents: automatic fast-track with no adjuster visit · If no response in 7 days: escalate to full investigation with prepared context · Traceability exportable aligned with relevant duty-of-care requirements and the EU AI Act
or, if reliability is lower or ISA flags a higher-risk segment
→ The agent routes to the adjuster: model score, ISA segment risk profile, CF documents that would resolve the case, and the economic function with the cost of each option · The adjuster decides in minutes with judgement, not by default
The agent does not choose between pay or investigate: it chooses the lowest expected-cost action for each specific claim. When it cannot act with guarantees, the adjuster receives a pre-built file — not a raw score.
ActionPDF

Illustrative example. Each deployment is adapted to each insurer’s models, data, and operating procedures.

Estimated portfolio impact · 10,000 claims/year
€1.1M
Annual operating cost saving
Vs investigating edge cases by default · €335 × 3,300 redirected claims
67%
Claims resolved with no human intervention
Direct auto-settlement in full-reliability cases
48h
Fast-track resolution time
Vs weeks in full investigation · Direct NPS impact