AI Solutions

AI that works — practical intelligence for measurable business outcomes.

Most AI initiatives fail because they treat technology as the solution rather than the enabler. Burt Consultants delivers AI capability that integrates with your organisation, your data, and your people to produce results that matter.

View AI case studies

The challenge

Why most AI initiatives fail to deliver ROI.

85% of AI projects fail to deliver projected returns. The failure modes are predictable.

01

Unclear objectives

Duplicated spend from uncoordinated department purchases without strategic alignment.

02

Governance incidents

Unapproved model usage creating compliance risk and reputational exposure.

03

Strategic drift

Local efficiencies that never compound into organisational capability or competitive advantage.

Our methodology

Four-phase approach to AI that delivers.

Discover

Assessment of readiness, data maturity, and opportunity identification with clear ROI modelling.

Design

Solution architecture with governance integration, success criteria, and stakeholder alignment.

Deliver

Implementation with stage gates, change management, and iterative validation against business outcomes.

Develop

Continuous improvement, model monitoring, capability building, and knowledge transfer.

Service cluster

AI Workplace Solutions

Intelligent automation designed for measurable productivity improvement with responsible governance.

Intelligent Workflow Automation

Process identification, RPA integration, intelligent document processing, and human-in-the-loop design.

Typical outcomes
  • 40-60% reduction in processing time
  • Error elimination and staff capacity release
Use cases: Financial services, healthcare, manufacturing, customer onboarding

Document Processing & Knowledge Management

NLP-powered extraction, classification, semantic search, and knowledge graph construction.

Typical outcomes
  • 90%+ reduction in document processing time
  • Improved compliance and faster decisions
Use cases: Contract review, regulatory filing, research synthesis, institutional knowledge

Predictive Analytics for Operations

Demand forecasting, resource optimisation, anomaly detection, and risk prediction.

Typical outcomes
  • Improved forecast accuracy
  • Reduced waste and proactive risk management
Use cases: Inventory planning, predictive maintenance, churn prediction, fraud detection

AI-Powered Customer Engagement

Conversational AI, personalisation engines, sentiment analysis, and next-best-action recommendation.

Typical outcomes
  • 24/7 service availability
  • Improved satisfaction and reduced service costs
Use cases: Customer service automation, sales assistance, personalised marketing

Service cluster

AI Strategy & Governance

Strategic advisory that ensures AI investments are aligned, governed, and sustainable.

AI Readiness Assessment

Organisational evaluation across data maturity, technical infrastructure, talent, and culture.

Typical outcomes: Clear prioritisation roadmap, risk identification, and investment justification.

Responsible AI Framework

Governance structures for fairness, transparency, accountability, and human oversight.

Typical outcomes: EU AI Act compliance, risk mitigation, stakeholder confidence, and audit readiness.

Model Selection & Vendor Evaluation

Structured assessment of build-vs-buy, vendor capabilities, and fit-for-purpose evaluation.

Typical outcomes: Optimal technology decisions, avoided vendor lock-in, and cost optimisation.

AI Literacy Training for Leadership

Executive and board education on AI capabilities, limitations, and strategic implications.

Typical outcomes: Informed decision-making, realistic expectations, and effective oversight.

Service cluster

AI Implementation & Integration

Technical delivery that bridges the gap between AI ambition and production reality.

Custom AI Solution Development

Bespoke ML engineering, NLP, computer vision, and generative AI applications.

Typical outcomes: Differentiated capability, competitive advantage, and IP development.

Legacy System AI Enhancement

API integration, microservices architecture, gradual modernisation, and intelligent augmentation.

Typical outcomes: Extended asset life, improved functionality, and reduced replacement risk.

CI/CD for Machine Learning (MLOps)

Automated training pipelines, model versioning, A/B testing, and production monitoring.

Typical outcomes: Reliable model performance, rapid iteration, and scalable deployment.

Continuous Model Monitoring

Drift detection, automated alerting, retraining triggers, and feedback loop integration.

Typical outcomes: Sustained accuracy, early problem detection, and regulatory compliance.
Get started

Ready to make AI work for your business?

Book a discovery call to discuss your AI readiness, explore opportunities, and understand how our integrated approach delivers where point solutions fail.

View proof points