Data governance
We define access, retention and deployment requirements for each system, including encryption in transit and at rest. We select services and deployment settings that exclude client data from public model training.
Campabalt combines business analysis, systems design and
engineering to develop AI and automation for business operations.
Our work spans research and advisory, implementation and operational support.
// What We Do
Our work connects business analysis with systems design, engineering and operational support.
Engagements can address a defined stage or continue through implementation.
/ 01 Assess
Research & analysis
We study business processes, analyze data and assess operational constraints. The findings establish where AI and automation are useful, what is feasible and which priorities merit further work.
/ 02 Design
Systems & solution design
We define the architecture, data flows and integration requirements. Tasks, dependencies and approval points are established before development, including where staff need to contribute operational knowledge.
/ 03 Build
AI engineering & integration
We develop software, automation workflows and AI capabilities, and integrate them with existing systems. Testing uses representative operational data and agreed performance criteria.
/ 04 Run
Deployment & operational support
We deploy systems into live operations and establish the documentation, training and support needed for continued use.
// Capabilities
We develop capabilities for business data, communication and operational decisions.
Each can be introduced individually or connected with others through shared data and workflows.
We connect data from business systems and establish consistent definitions for reporting and analysis. Shared dashboards provide visibility across processes, performance and resources.
We convert invoices, orders, forms, contracts and case documents into structured records and check them against source systems. Exceptions are flagged for review, and changes are logged.
We model demand, capacity, resources and budgets using business data. Forecasting and optimisation models support planning, scheduling and allocation, while AI interfaces let teams explore scenarios and review assumptions in plain language.
We connect pricing rules and contract terms with current costs, demand and margin requirements. Proposed changes are evaluated across affected products and services before approval and application.
We classify inbound email, forms and messages by subject, urgency and responsible team. Responses are drafted from approved records and routed for review before sending.
We organise reviews, complaints, surveys and service feedback into structured insight. Analysis identifies recurring themes by product, service, location or period, with significant issues routed for review.
We connect data from business systems and establish consistent definitions for reporting and analysis. Shared dashboards provide visibility across processes, performance and resources.
We convert invoices, orders, forms, contracts and case documents into structured records and check them against source systems. Exceptions are flagged for review, and changes are logged.
We model demand, capacity, resources and budgets using business data. Forecasting and optimisation models support planning, scheduling and allocation, while AI interfaces let teams explore scenarios and review assumptions in plain language.
We connect pricing rules and contract terms with current costs, demand and margin requirements. Proposed changes are evaluated across affected products and services before approval and application.
We classify inbound email, forms and messages by subject, urgency and responsible team. Responses are drafted from approved records and routed for review before sending.
We organise reviews, complaints, surveys and service feedback into structured insight. Analysis identifies recurring themes by product, service, location or period, with significant issues routed for review.
// AI Orchestration In Practice
AI orchestration coordinates interdependent tasks across systems and teams. It carries validated information and staff input between workflows, routes exceptions and brings the relevant analysis together for a decision.
Illustrative example: a food business serving commercial and retail customers reviews a supplier cost change. Sales, inventory and contract information inform pricing options for management review.
Staff contribute information the records may not contain, such as a supplier commitment or a customer-specific restriction. Authorised managers approve pricing changes and customer communications; exceptions return for review.
// Our Approach To AI
We define what each AI system may access, which actions it may take and where human approval is required.
These controls are designed into the system and reviewed throughout its use.
We define access, retention and deployment requirements for each system, including encryption in transit and at rest. We select services and deployment settings that exclude client data from public model training.
Each agent has a defined task, a restricted set of tools and explicit limits on its actions. Sensitive actions require approval, and actions outside the permitted scope are blocked.
Named people are responsible for reviewing exceptions and approving consequential actions. Staff contribute context the system may lack. Safety-critical and regulated decisions remain with authorised people, with escalation and fallback procedures defined for critical workflows.
We monitor system activity, exceptions and approvals. Logs retain source references, relevant system and model versions, and approval records to support investigation and escalation.
// How We Build
We work with the teams responsible for the operation, agree release criteria and introduce systems in stages.
Training, documentation and support accompany implementation.
We work with operational teams during implementation and rollout, including on-site collaboration where the work requires it.
Training covers system use, interpretation of outputs and how to contribute information the system lacks. Staff receive operating guides and learn to recognise missing context, changed assumptions and situations requiring escalation.
We support the system in use, review feedback with your team and maintain and evolve integrations. Updates are tested and documented before release, with rollback procedures in place.
// About Campabalt
Campabalt brings business analysis and technical delivery together within one practice. The people who define the work remain involved in its implementation, connecting operational judgment with engineering decisions.

Chairman
Ilia oversees Campabalt’s strategic direction, governance and major commercial commitments.

Chief Executive Officer
Maria leads Campabalt’s day-to-day operations and oversees client engagements.

Chief Technology Officer
Denys leads Campabalt’s systems architecture, engineering and technical delivery.

Head of Visual Communications
Sofiya leads Campabalt’s graphic design and visual communications.
// Contact
For enquiries about advisory work, systems development or operational support,
contact [email protected] or use the form below.