Case studies

Anonymised work, real operating problems.

These examples show how AIA turns legacy systems, manual review, and repeated operational work into practical AI workflows with human control.

Transport and equipment SaaS

AI-enabled fleet diagnostics

Bottleneck

Service and unit context lived across a complex legacy database, making technician-ready insight hard to reach.

Built

An intelligent diagnostics layer with unit history, repeat-fault review, and data-backed versus estimated labels.

Control

Every insight is labelled so users can see what came from source data and what was estimated.

Why it matters

Turns buried service history into faster workshop decisions without replacing technician judgement.

Equipment finance and leasing

AI credit decision pipeline

Bottleneck

A credit manager had to manually inspect application packs and repeat the same decision checks under time pressure.

Built

A 4-stage assessment workflow mapped to 16 existing credit checks, producing reviewable recommendations and risk notes.

Control

The AI recommends with source traceability; the human remains the final decision maker.

Why it matters

Moves assessment work toward minutes while preserving auditability and lending control.

Construction intelligence SaaS

AI project health analysis

Bottleneck

Large project datasets could show margin erosion and delivery risk, but the useful signals were buried across schemas.

Built

Real-data analysis pipelines that produce structured project health assessments and lineage back to source fields.

Control

Numbers and claims are tied back to source tables and reviewable analysis steps.

Why it matters

Turns project data into early warning signals leadership can act on.

Insurance brokerage

AI content factory

Bottleneck

Brand assets existed, but turning them into consistent multi-channel social content was slow and manual.

Built

A content workflow that generates platform-specific creative assets and publishes across social channels.

Control

Scheduling, review, publishing, and synced post management stay visible to the business.

Why it matters

Creates a repeatable marketing operation without hiring a larger content team.

Start with your version of this.

Bring one workflow, one bottleneck, or one repeated decision. The first step is a practical prototype, not a large integration.

Start with one workflow