Move AI from experiment to production
AI can create measurable value, but only when the use case, data, security, architecture and operating model are clear. We help Microsoft-centric organisations prioritise AI opportunities, stabilise prototypes, automate workflows and build secure Azure-native AI systems that are ready for real users.
You need AI value without uncontrolled production risk
You have AI demand but no clear roadmap.
You have a PoC that works in demo but is not production-ready.
Teams are using AI informally and governance is unclear.
You want to automate a document-heavy, email-heavy or decision-heavy workflow.
You need a secure enterprise knowledge assistant over approved internal content.
Risk, security or architecture stakeholders need confidence before rollout.
Choose the right AI starting point
Explore AI services designed to help Microsoft-centric organisations whether it's about enterprise AI knowledge assistants, assessing readiness, trusted data foundations with Microsoft Fabric, or turning your AI PoC into a real product.
AI Readiness Assessment
If you have an AI prototype that doesn't work well, we assess your AI's use cases, data, architecture and governance before scaling into production.
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AI Prototype to Production
Turn promising AI prototypes into secure, governed Azure solutions that can support real users.
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Microsoft Fabric Proof of Value
Prove Fabric value with ingestion, lakehouse structure, Power BI reporting and a practical scale roadmap.
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Enterprise AI Knowledge Assistant
Internal Enterprise AI Assistants are essential if you have knowledge in various sources in your organisation. Combine them into one secure and governed AI system.
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AI isn't the hard part - getting it to actually work is.
We deliver production-ready AI solutions that are secure, scalable, and built for long-term success.
Azure-native identity & permissions
Entra ID and RBAC preserve organisational access controls.
Human-in-the-loop workflows
AI prepares and recommends while humans remain accountable.
Monitoring & incident paths
Logs, alerts and escalation processes are designed before go-live.
Maintainable after handover
Documentation and knowledge transfer reduce vendor dependence.
AI & Automation packages
Start with a focused assessment, pilot or productionisation sprint before committing to a wider AI programme.
AI Production Readiness Assessment
Score readiness, prioritise use cases and define a practical roadmap to pilot, MVP or production.
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AI Prototype Productionisation
Stabilise architecture, data, identity, evaluation, monitoring, cost control and operational readiness.
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AI Workflow Automation PoC
Automate one workflow with AI assistance, human review, auditability and secure data handling.
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Secure Enterprise Knowledge Assistant Pilot
Build a permission-aware assistant with approved sources, citations, feedback and usage analytics.
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AI Governance and Production Readiness Review
Review security, privacy, responsible AI, access controls, logging, evaluation, cost and operations.
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Decision Support and Evaluation Automation Pilot
Extract evidence, support scoring and generate explainable recommendations while keeping decisions controlled.
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AI systems delivering measurable value in real workflows
Selected examples of how we have validated AI use cases, automated document-heavy workflows and turned promising prototypes into governed Azure solutions.
Legal technology
Legal inbox assistant delivered in 10 days
Situation
A legal-technology team needed to reduce shared-inbox administration and connect emails, approved legal content and Jira work items without disrupting existing legal workflows or removing human oversight.
Solution
We delivered a modular Azure-based assistant that ingested incoming email, retrieved relevant legal content, drafted responses and created structured Jira tasks, with mandatory human review before action.
Benefits
- Delivered as a working PoC in 10 days.
- Reduced manual inbox triage by 40-60% during testing.
- Produced draft responses in seconds and created a clear path to MVP.
Construction workforce compliance
AI document validation at scale
Situation
A major solutions provider operating in a highly regulated industry needed to process a substantial amount of scanned documents across roughly 1,000 document types. Inconsistent scans, layouts and data quality made manual extraction and validation slow and error-prone.
Solution
We built an Azure document-processing pipeline that extracted and normalised key fields, applied validation rules and flagged missing, incorrect or expired information for human review.
Benefits
- Reduced administrative workload by more than 75%.
- Automated high-volume document processing and revalidation.
- Improved compliance visibility, alerts and auditability.
Global operations
Enterprise knowledge assistant rebuilt for production
Situation
An internal “chat with your data” prototype had demonstrated user value, but the generated architecture raised concerns around identity, data residency, cost control, performance, observability and maintainability.
Solution
We redesigned and rebuilt the prototype as a secure Azure-native MVP with enterprise identity, controlled access, monitoring, deployment automation and integration with the organisation’s existing knowledge sources.
Benefits
- Delivered a governed enterprise MVP in two sprints.
- Reduced technical and operational risk before wider rollout.
- Created a supportable foundation for multilingual and future assistant capabilities.
FAQ
Can you help if we already have an AI prototype?
Yes. We can review the prototype, identify production-readiness gaps and define whether it should be stabilised, refactored or rebuilt for secure Azure operation.
Can AI stay inside our Azure environment?
Yes. We design Azure-native AI systems with identity, access control, monitoring, auditability and security requirements built in from the start.
How do you reduce AI risk?
We define approved data sources, human review points, access controls, evaluation criteria, logging, cost controls and operational ownership before production rollout.
Do you build fully autonomous agents?
Where appropriate, but we do not recommend uncontrolled automation for high-risk workflows. We usually design human-in-the-loop processes first, then expand autonomy only where risk and value justify it.
If you are not sure what your organisation needs regarding AI solutions, book a free consultation with us, and we help you decide!
Book a free AI consultation