Why we organise delivery by industry
AI in financial services is not the same problem as AI in clinical operations. Domain-specific practice leads, regulatory posture, and reference architectures keep delivery anchored to where the business actually runs.
Domain-led teams
Each industry is led by practitioners with regulated-enterprise delivery experience in that sector — not generalists learning the domain on your program.
Reference architectures
Pre-validated patterns for the most common production AI shapes in each vertical, so delivery starts from proven ground.
Regulatory fluency
Compliance and audit posture sit in the delivery method itself — not in a separate workstream added at the end.
Sectors where a decision must be explainable, auditable, and owned by a human before it ever ships.
Financial Services
Credit, fraud, AML, and customer intelligence with governed model risk and a full audit trail.
Regulatory contextRBI, PCI-DSS, internal model governance, and auditability
View industry practiceHealthcare & Life Sciences
Clinical decision support, document intelligence, and operations AI with privacy-aware controls.
Regulatory contextHIPAA-aligned controls, privacy posture, and clinical review safeguards
View industry practiceLegal & Compliance
Contract analysis, privileged document workflows, and retrieval with citation enforcement.
Regulatory contextPrivilege boundaries, review traceability, and governed document handling
View industry practiceGovernment & Public Sector
Document processing, eligibility workflows, and public-sector AI with human-in-loop accountability.
Regulatory contextPolicy traceability, human review, and public-sector assurance expectations
View industry practiceSectors where AI is judged on operational reliability and measurable commercial outcome.
Manufacturing
Predictive maintenance, defect detection, and yield optimisation tied to plant-level workflow.
Regulatory contextOperational resilience, quality traceability, and plant-level change control
View industry practiceRetail & E-Commerce
Personalisation, demand forecasting, and margin-aware recommendation systems.
Regulatory contextConsent, personalization controls, and margin-aware operations
View industry practiceLogistics & Supply Chain
Forecasting, routing, and exception detection with SLA-grade reliability.
Regulatory contextSLA visibility, route accountability, and operational exception handling
View industry practiceMedia & Entertainment
Rights-aware content operations, moderation pipelines, and metadata enrichment at scale.
Regulatory contextRights-aware workflows, moderation controls, and governed content operations
View industry practiceNot sure which fits
Talk to a practice lead in your sector.
A 40-minute conversation about your sector constraints, regulatory posture, and the highest-value AI use case to sequence first.