AI Audit & Strategy
Identify where AI can create value, what your organisation can realistically deploy and where to invest first. OLING develops an AI maturity assessment and roadmap aligned with business priorities.
Consulting, Project Advisory, Engineering & AI Governance
AI & Transformation
OLING supports businesses and public organisations through AI transformation, from assessment and strategy to operational integration, organisational management and performance monitoring.
Discuss your AI projectIntegrate AI into how your organisation actually works
Our approach combines organisational consulting, project advisory, engineering, data, IT integration and governance. We start with a business process, its people and constraints to design something useful, controllable and operable. ERP, CRM, maintenance, finance and BI programmes provide the context in which AI must fit.
Six services from strategy to operations
Organisational Transformation & AI Operating Models
Transforming a process with AI means redesigning work, accountability and management. OLING connects the target operating model with team practices, business applications and performance objectives.
AI Project Advisory & Delivery Management
Support the project owner from business requirements to operational launch. OLING applies its ERP, finance, CRM, maintenance and BI project advisory experience to AI, with independent solution selection and evidence-based acceptance.
AI Architecture, Engineering & Integration
Integrate AI with existing applications through an operable, secure and reversible architecture. OLING provides technical studies, engineering support and integration to connect models with business processes and data.
AI Governance, Security & Compliance
Establish controlled AI use with clear accountability and proportionate safeguards. OLING connects AI governance, the AI Act, GDPR, cybersecurity and an AI management system based on ISO/IEC 42001.
Fractional AI Leadership & Programme Management
Give your AI programme accountable leadership, a delivery rhythm and a clear trajectory. OLING acts as programme director or fractional AI lead, supporting executive management, business teams and IT.
AI in your business processes
AI for Executive Management and Business Steering
Prepare performance reviews, reconcile indicators and explore scenarios while keeping synthesis separate from decision-making.
AI for Finance, Accounting and Procurement
Reduce processing effort and strengthen controls without delegating accounting approval or payment authority to a model.
AI for Customer Service and CRM
Classify requests, assist responses and understand complaints while maintaining control over customer relationships.
AI for Human Resources
Improve access to HR procedures and reduce administrative effort while protecting people and their data.
AI for Production, Operations and Maintenance
Help technicians find the right information, structure field reports and anticipate incidents where data supports it.
AI for Quality, Audit and Compliance
Prepare controls and connect evidence to requirements without automating the auditor’s judgement.
Enterprise RAG and Knowledge Management
Retrieve reliable information from internal documents and make knowledge accessible to authorised users.
AI for Data and Business Intelligence
Enrich analysis and forecasting while maintaining control over definitions, calculations and data quality.
Transform work, accountability and management
Target-process example: a customer request arrives in the CRM. An agent classifies it, retrieves permitted information and prepares a draft with sources. An adviser checks the context, edits and approves sending. The manager monitors corrections, end-to-end time and escalations. Missing data or an out-of-scope request sends the case back to a human workflow. This illustrates the method, not a documented customer deployment.
Our method: from business need to measured value
Understand
Analyse the organisation, activities, people, data and IT landscape. Observe real work and pain points before selecting a solution.
Prioritise
Compare business value, feasibility and risk. Establish a baseline, a business owner and success criteria for each use case.
Design
Define the target process, architecture, interfaces, responsibilities, human approvals and performance indicators.
Experiment
Test a pilot on representative situations, including failure cases. Compare quality, cost and usefulness with agreed criteria.
Deploy
Integrate with applications, run acceptance and rollback checks, train users and support managers.
Measure
Track benefits, errors, costs, adoption and incidents. Regularly reassess models, data and controls.
Architecture matched to the need
Rules and workflows for deterministic tasks; machine learning for history-based predictions; RAG for grounded document answers; agents for controlled sequences of actions. We assess data quality, permissions, interfaces, costs and operating requirements before selecting cloud, private or hybrid architecture.
Sector context and governance throughout
Water and wastewater, ports, transport and logistics, industry, trade and distribution, public bodies and training providers: business constraints, data criticality and operating conditions shape the scope. Project advisory, process and compliance experience is distinguished from confirmed AI work. Security, data protection and human oversight run through all six stages.
FAQ
What does an enterprise AI audit cover?
An inventory of uses, an assessment of data, IT and organisational readiness, process analysis and use-case prioritisation. Findings specify risks, prerequisites and an investment trajectory.
How can AI be integrated into an ERP?
Define a specific task, assess data and APIs, separate reads from writes, then test a connector with restricted permissions. Consequential writes and decisions require approval, logging and rollback.
How can AI agents be deployed reliably?
Constrain tools and permissions, test adversarial and failure scenarios, require appropriate human approvals and monitor actions. An agent must be able to stop and hand a case to a person.
How should an AI programme be measured?
Compare outcomes with a baseline: quality, end-to-end time, total cost, adoption and incidents. Measure review effort and errors, not just the number of generated answers.
Our experience and engagements
FORMELEC — AI assessment and reporting agents
AI assessment and agent-based data consolidation work for reporting. Scope confirmed by OLING. No quantified outcomes or company-wide industrial rollout are claimed.
Trading and distribution company — AI assessment and reporting agents
AI assessment and agent-based data consolidation work for reporting. Scope confirmed by OLING. No quantified outcomes or company-wide industrial rollout are claimed.