05
AI Solutions
We implement practical AI use-cases that save time and reduce workload, while keeping access control, logging and safe usage boundaries in place.
What this service solves
Most organisations want AI, but fear misuse, hallucations and data leakage. Uncontrolled AI
creates more risk than value.
- Apply AI only where it delivers clear value
- Ensure answers are traceable and auditable
- Prevent misuse through guards and control
- Integrate AI into real workflows, not demos
What we do
01
Build AI Assistants
Create assistants designed for specific, controlled use-cases.
• Internal SOP and policy assistants (traceable responses)
• Knowledge Q&A with citations and source references
• Role-based access to information
• Context-aware response limits
02
Support & Ops Assistants
Reduce repetitive workload in customer and admin teams.
• Support triage and draft responses
• FAQ and internal query handling
• Escalation rules and human-in-the-loop flows
03
AI-Driven Automation
Use AI to process information at scale.
• Summarisation and classification
• Routing and prioritisation
• Key-field extraction from documents
• Structured output for downstream systems
04
Guardrails & Governance
Ensure AI is safe, auditable and controllable.
• Access control and permissions
• Logging and traceability
• Prompt safety and response constraints
• Usage boundaries and policies
05
Evaluation & Readiness
Validate reliability before rollout.
• Test sets and evaluation criteria
• Accuracy and failure analysis
• Risk notes and mitigation steps
• Deployment readiness checks
How we work
01
Identify
Select high-value, low-risk use-cases.
02
Design
Define workflows, guardrails and evaluation criteria.
03
Prototype
Build and integrate the AI solution.
04
Evaluate
Test outputs, edge cases and misuse scenarios.
05
Deploy
Roll out with monitoring and controls.
Typical Deliverables
✓ Use-case design and risk
notes
✓ AI prototype and integration
plan
✓ Knowledge base configuration
(if applicable)
✓ Guardrails and admin controls
(optional)
✓ Evaluation checklist and test
set
Suitable for
- Teams with heavy SOP or document usage
- Support and admin teams handling repetitive queries
- Organisations wanting AI with governance-ready setup
- Enterprises preparing for responsible AI adoption
FAQ
Any system that uses machine learning, natural language processing or computer
vision to automate decisions or generate insights that previously required
manual effort.
Both. We implement LLM-based generative agents and traditional predictive
models/classification systems.
We typically use open-source or commercial base models and fine-tune or augment
them (RAG) with your specific data for the best cost-to-performance ratio.
Integration is connecting to a service (like OpenAI). Custom development is
building specialized logic, fine-tuning models or creating unique agentic
workflows tailored to your business.
Usually via time saved, reduction in error rates or the ability to process data
at a scale previously impossible for human teams.
We implement guardrails, validation layers and monitoring to detect and
mitigate biased or hallucinated outputs.
Yes. We build AI-powered features that sit within your current tech stack.