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BritonOne Technology
Case studies

AI & Machine Learning

Production AI that clears model-risk review: generative, agentic, and classical ML, grounded and audit-ready from day one.

AI & Machine Learning case studies
Underwriting copilot for a speciality insurer
Insurance

Underwriting copilot for a speciality insurer

Drafted first-pass quotes from submission packs 3.1x faster, every clause cited back to the wording it came from.

PythonAzure OpenAILangChainPostgres
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Clause-level contract drafting for a commercial law firm
Legal

Clause-level contract drafting for a commercial law firm

Cut first-draft time on regulated commercial contracts by 61%, each clause traceable to firm precedent.

TypeScriptAWS BedrockAnthropicOpenSearch
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Grounded knowledge copilot for a retail bank contact centre
Banking

Grounded knowledge copilot for a retail bank contact centre

Cut average handle time 44% across 2,600 agents, with answers grounded in approved policy only.

PythonAzure OpenAIAzure AI SearchKubernetes
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Autonomous reconciliation for a payments processor
Fintech

Autonomous reconciliation for a payments processor

Resolved 89% of reconciliation breaks without a human, every action logged for audit.

PythonTemporalLangGraphPostgres
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Self-healing incident remediation for a manufacturer's OT platform
Manufacturing

Self-healing incident remediation for a manufacturer's OT platform

Cut median incident remediation from 41 to 7 minutes across a manufacturer's OT platform, with a human approval gate on every action.

GoKubernetesLangGraphPrometheus
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Agentic procurement triage for an NHS trust
Healthcare

Agentic procurement triage for an NHS trust

Routed and matched 73% of purchase requests end to end, escalating only genuine exceptions.

PythonLangGraphAzureSQL Server
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Churn prediction for a foodtech subscription platform
Foodtech

Churn prediction for a foodtech subscription platform

Cut voluntary churn 18% in two quarters with next-best-action scoring for a meal-subscription platform.

PythonXGBoostSnowflakedbt
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Explainable credit scoring for a digital lender
Fintech

Explainable credit scoring for a digital lender

Lifted approval rates 31% at constant loss, every decision reason-coded for the FCA.

PythonLightGBMSHAPAWS SageMaker
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Demand forecasting for a grocery retailer
Retail

Demand forecasting for a grocery retailer

Cut waste 22% across 900 stores with SKU-level probabilistic forecasts.

PythonPyTorchDatabricksDelta Lake
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Complaints triage and root-cause tagging for a government department
Government & Public

Complaints triage and root-cause tagging for a government department

Auto-classified 58% of citizen complaints to root cause, feeding the department's reporting directly.

PythonspaCyTransformersPostgreSQL
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Adverse-media screening for a private bank
Wealth Management

Adverse-media screening for a private bank

Screened 12x more names at a lower false-positive rate, each hit evidenced.

PythonTransformersElasticsearchAzure
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Motor damage assessment from photos for an insurer
Insurance

Motor damage assessment from photos for an insurer

Settled 47% of motor claims from images alone, with fraud flags surfaced inline.

PythonPyTorchDetectron2AWS
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Shipping-document extraction for a logistics operator
Logistics

Shipping-document extraction for a logistics operator

Achieved 94% straight-through extraction on bills of lading and customs paperwork for a logistics operator.

PythonLayoutLMTesseractAzure
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AI governance and model-risk framework for a pharma company
Pharma

AI governance and model-risk framework for a pharma company

Stood up a board-ready AI governance and model-risk framework for a pharma company in 9 weeks, cleared at first internal audit.

GovernanceModel riskGxPEU AI Act
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GenAI opportunity assessment for an insurance group
Insurance

GenAI opportunity assessment for an insurance group

Mapped a £14M annual benefit pipeline across 40 use cases, sequenced by risk.

StrategyValue modellingRisk assessment
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FAQs

Questions about our case studies

Frequently asked questions

Yes. Every case study is a real programme we delivered. We anonymise client names and identifying details where confidentiality requires it, but the challenges, approaches, and outcomes are as they happened.

Next step

Get a senior architect on the call, first time, every time.

No SDR gauntlet. 30 minutes with an engineer who can scope the problem, name the risks, and give you an honest feasibility call.