Enterprise knowledge
Find answers in approved documents with source references and access checks for each source.
Data Management IG
Well-engineered AI integration into business processes
Data Management IG connects AI with enterprise data, systems, and workflows. We design integrations around security requirements, user permissions, and measurable outcomes.
Choose a process for the first pilot
These are scenarios for assessment and design. Solution scope, feature availability, and expected impact are agreed after reviewing the client's systems and data.
Documents and requests
Classify documents, extract fields, check completeness, and prepare responses for staff review.
ERP and CRM operations
Prepare records and tasks, validate data, and perform permitted steps through controlled integrations.
System operations
Analyse events and recurring incidents, identify deviations, and prepare recommendations for the responsible team.
From data to a verified action
Logical integration architecture. We select AI, rules, or a combination for each task; every action stays within agreed permissions.
Enterprise sources
ERP, CRM, documents, knowledge bases, events, and equipment.
Data and access
Quality, freshness, permitted context, and user access checks.
AI and rules
The model analyses data; rules constrain its tools and permitted operations.
Controlled action
Output validation, approval by the responsible person, and execution through APIs.
Evaluation and support
Activity logs, quality, cost, incidents, and model change control.
Security by design
Security requirements shape the architecture
Before work starts, we identify applicable legal, sector, and contractual requirements, data classes, threats, and owners. Agreed requirements become controls and acceptance criteria.
Data protection
Data minimisation, encryption, retention, and deletion. We agree processing locations, third-party transfers, and the model provider's terms for using data.
Least privilege
Access to sources and actions is checked by the application and APIs. Agent tools are restricted; consequential actions follow a defined approval process.
Pre-release evaluation
We test quality on agreed examples, data leakage, prompt injection in documents, and invalid tool calls. AI outputs are validated before entering other systems.
Managed operations
Privacy-aware activity logs, cost monitoring, and model change control. We define incident response, automation shutdown, and a fallback to manual processing.
International standards and regulatory references
Standards and guidance inform control design. Legal obligations depend on jurisdiction, participants' roles, and intended use. Certification and conformity claims require separate assessment and documentary evidence.
- ISO/IEC 27001:2022
- Information security management: risks, responsibilities, and controls for protecting information.
- ISO/IEC 42001:2023
- AI management systems: responsible development, deployment, use, and improvement.
- ISO/IEC 23894:2023
- Guidance for managing AI risks in the organisation's context.
- NIST AI RMF / GenAI Profile
- A voluntary framework for identifying, assessing, and managing risks, with a dedicated generative AI profile.
- OWASP GenAI / Agentic Security
- Practical guidance on prompt injection, data leakage, tool misuse, and excessive agent permissions.
- GDPR
- Where applicable: lawful and purpose-bound personal data processing, minimisation, protection by design, and individuals' rights.
- EU AI Act
- Where applicable: intended use and system risk category, provider or deployer role, transparency, and relevant obligations.
From assessment to everyday use
Readiness assessment
Map the process, sources, permissions, security requirements, and baseline metrics. Deliver a prioritised scenario and pilot plan.
One-process pilot
Evaluate integration, quality, and action controls using agreed data. Compare outcomes with the baseline and decide whether to scale.
Deployment and support
Integrate with production systems, train the team, and agree ownership, monitoring, and change procedures.
Measure the time and full cost of a correctly completed operation: data preparation, integration, computation, human review, error correction, and ongoing support.
Our product
AZIOT: equipment data and AI
Data Management IG develops AZIOT, an AI-enabled IoT platform for infrastructure monitoring and control. Applied directions include deviation analysis, unusual resource consumption, and operator recommendations.
Specific AI capabilities and their effectiveness are validated through pilots using facility data. Equipment access and automatic actions follow agreed rules.
AZIOT architectureFor complex projects, we bring in specialist capabilities from Intecracy Group companies. Solution scope, responsibilities, and ongoing support are agreed with the client.
Intecracy Group strategy ↗Next step
Let’s apply our expertise to your challenge
Tell us about the project and we will propose a practical approach.