Manual repetitive workflows
Staff spend time on approvals, data entry and routing that automation could handle.
Intelligent workflows
Automate the repetitive work without automating away control.
The best automation targets are the boring, high-volume, rule-heavy tasks — triage, routing, summarizing, data entry. We build AI automations for exactly those, with clear boundaries on what runs unattended and what needs a human check. The goal is hours saved, not a black box no one trusts.
Discuss AI Automation
Architecture
flowchart LR
ID[Entra ID] -. auth .-> APP
subgraph VNET[Private VNet - no public egress]
APP[Your App] --> PE[Private Endpoint]
end
PE --> AOAI[Azure OpenAI]
AOAI --> DATA[Your Data - RAG]
MON[Cost and Usage Monitor] -. watches .-> AOAI
Business challenges
AI Automation challenges we solve.
Every recommendation starts with business pressure, technical risk and the operating model required after launch.
Automation without oversight
Existing automations run without human checkpoints for higher-risk actions.
Disconnected tools
Business systems, cloud services and approved AI tools are not wired together.
Solution overview
AI Automation designed for production readiness.
We build AI automations for exactly those, with clear boundaries on what runs unattended and what needs a human check. The goal is hours saved, not a black box no one trusts.
Workflow mapping
Document the manual steps, decision points and systems involved in the process.
Automation design
Decide what can run unattended and what still needs a human check.
Human approval gates
Keep a checkpoint on higher-risk actions before they complete.
Operational controls
Connect business systems, cloud services and AI tools into one monitored workflow.
Architecture model
A practical delivery architecture before implementation begins.
We define the target operating model, controls, integration points and ownership path before building, so the solution can be supported after launch.
CloudevTech
Enterprise delivery model
01
Discover
02
Architect
03
Implement
04
Validate
05
Operate
Our approach
Structured delivery from discovery to operational handover.
Every engagement is shaped around the service goal, current constraints and the operating model your team needs after launch.
Map the workflow
Document the manual steps, decision points and systems involved in the process.
Design automation and gates
Decide what can be fully automated and where a human approval step is still needed.
Build and integrate
Connect the relevant business systems, cloud services and AI tools into one workflow.
Monitor and adjust
Track automation performance and refine as processes change.
Business benefits
Outcomes designed for decision makers and delivery teams.
Benefits are framed around measurable improvement, operating confidence and reduced delivery risk.
Reduced manual workload
Automated workflows handle repetitive steps so staff focus on judgment work.
Human approval gates
Higher-risk actions keep a human checkpoint before completion.
Connected systems
Business processes, cloud services and AI tools work from one automated workflow.
Technology stack
Implemented with proven platforms and tools.
Technology choices are confirmed during discovery, with a preference for reliable, maintainable platforms your team can support.
Power Automate
Copilot Studio
Azure Functions
Logic Apps
APIs
FAQ
Common questions before engagement.
Short answers to common planning questions for AI Automation.
Where should we start?
The highest-volume, lowest-risk repetitive task. Prove value there before automating anything sensitive.
What if the AI gets it wrong?
We design in human review at the points where a mistake would actually matter.
Enterprise consultation
Book a consultation