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Case Studies

Results that hold.

Real engagements. Measurable outcomes. Client details withheld by agreement.

Technology

Product releases in 7 months

Delivered a 12-person augmented engineering team

A US-based B2B SaaS company with a 40-person internal engineering team was 4 months behind on a product roadmap that had already been communicated to enterprise customers. Hiring locally was taking 3 to 4 months per senior engineer. Amorisoft placed a 12-person augmented team covering backend, frontend, QA, and DevOps within 3 weeks of brief, fully embedded in the client's existing sprint cycles.

Staff AugmentationProduct EngineeringSaaS

Financial Services

Live AI deployments in 8 months

Built an AI governance framework for a Singapore asset manager

A Singapore-based asset management firm needed an AI strategy that could satisfy MAS regulatory expectations while delivering commercial returns. Amorisoft ran a 12-week advisory engagement covering governance, use case prioritisation, and vendor selection framework.

AI StrategyAI GovernanceRegulatory Alignment

Manufacturing

Funded AI initiatives

Defined an AI investment plan that resulted in 3 funded initiatives within 10 weeks of engagement close

A UAE-based industrial manufacturer with operations across 3 Gulf countries had no internal AI function. Amorisoft ran a 10-week advisory engagement, assessed the business from the ground up, and delivered a prioritised plan the leadership team could act on immediately.

AI StrategyInvestment PrioritisationVendor-Neutral Advisory

Retail

£2.1M

Projected first-year saving

Delivered a 3-year AI roadmap resulting in 4 approved AI initiatives in the first year

A UK-based retail group with 180 stores and an e-commerce operation had received 11 unsolicited AI vendor proposals in 8 months. Amorisoft was brought in to build an AI strategy from the ground up, independent of any vendor relationship.

AI StrategyTechnology RoadmapVendor-Neutral Advisory

Logistics

39%

Late delivery reduction

Reduced late deliveries by 39% using a predictive delay model built on 4 years of shipment and operational data

A US logistics operator running a ground distribution network was struggling with late delivery rates that had been climbing for 18 months. Amorisoft built a predictive ML model that flagged at-risk shipments 36 hours before scheduled delivery, giving dispatchers a window to act before a delay became a failure.

Predictive MLSupply Chain AIOperations Intelligence

Healthcare

28%

Readmission rate reduction

Reduced 30-day hospital readmission rate by 28% using a predictive discharge risk model

A public hospital network in Australia was facing persistently high 30-day readmission rates across its general medicine, cardiology, and orthopaedic wards. Amorisoft built a predictive ML model that scored each patient's readmission risk at the point of discharge, giving care coordinators a prioritised list for post-discharge follow-up every morning.

Predictive MLClinical Risk ScoringHealthcare AI

Education

34%

Dropout rate reduction

Reduced student dropout rate by 34% across 6 campuses using a predictive intervention model

A private university group operating 6 campuses across India was losing students to dropout at a rate that was costing both revenue and accreditation standing. Amorisoft built and deployed a predictive ML model that identified at-risk students 8 weeks before dropout typically occurred, giving academic advisors enough time to intervene.

Predictive MLEarly Warning SystemsEdTech

Insurance

4 hrs

Underwriting decision time

Cut underwriting decision time from 3 days to 4 hours

A Canadian property and casualty insurer used a generic LLM to assist underwriters with risk summaries. The model had no awareness of Canadian regulatory requirements, the insurer's internal risk appetite guidelines, or regional loss history patterns. Amorisoft fine-tuned a model on 8 years of policy, claims, and underwriter decision data to align risk scoring to the firm's actual appetite.

Custom Model TrainingDomain Fine-Tuning

Healthcare

64%

Report drafting time saved

Deployed a fine-tuned radiology reporting model that cut report drafting time by 64%

A radiology group with 4 imaging centres across Queensland trialled a general-purpose LLM for report drafting. The model used imprecise clinical language, could not handle the group's structured reporting templates, and got Australian spelling conventions wrong often enough to matter.

Custom Model TrainingDomain Fine-TuningRLHF

Financial Services

58%

False positive reduction

Cut false positive compliance alerts across a UK retail bank's compliance desk

A UK retail bank's compliance team processed 400 to 600 alerts daily from a generic LLM-based transaction monitoring layer. False positive rates ran above 70%, burning analyst hours and creating backlog. Amorisoft fine-tuned the model on 3 years of the bank's own adjudicated alert data.

Domain Fine-TuningCompliance AI

Legal Services

71%

Review time reduction

Reduced first-pass contract review time using a model fine-tuned on 14 years of firm precedent

A US litigation and corporate law firm ran a generic LLM across contract review. The model flagged irrelevant clauses, missed jurisdiction-specific risk language, and required constant attorney correction. Amorisoft fine-tuned a domain model on 14 years of the firm's own contract history, playbooks, and annotated review decisions, with RLHF cycles driven by senior associate feedback.

Domain Fine-TuningRLHFLegal AI

Manufacturing & Operations

63%

Inventory incidents down

Reduced demand-to-production lag from 4 days to under 2 hours

A US-based discrete manufacturer with a fragmented 5-system enterprise stack deployed a six-agent orchestration layer connecting SAP, Salesforce, MES, WMS, and a quality tool in real time without replacing any existing platform.

Multi-AgentSystem IntegrationOrchestration

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