AI Architecture, Engineering & Integration
Scope of our engagement
- LLMs, document RAG, classification, machine learning and predictive analytics as appropriate
- APIs, connectors, data pipelines, ETL and quality controls
- ERP, CRM, maintenance and document management integration; workflows and events
- AI agents with approved tools and multi-agent orchestration only where justified
- Cloud, SaaS, private or hybrid architectures according to constraints
- Evaluations, observability, versioning, MLOps/LLMOps and reversibility
Deliverables and decision criteria
Architecture pack, interface contracts, data flows, access models, evaluation datasets and deployment and operations procedures. We define latency budgets, cost limits, useful logs and recovery scenarios.
Prerequisites, controls and limitations
RAG requires reliable documents, permission-aware retrieval, cited sources and obsolete-document handling. Agents must constrain actions, isolate secrets and request approval before consequential operations. Forecasting requires usable historical data and drift monitoring.
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.
FAQ
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.