Business process automation and AI
Fewer manual steps. A process under control.
Connect tools and people around a bounded workflow, with controls, exceptions and approvals. AI where it helps.
Discuss this projectWhen it makes sense
- Requests move from forms and email to spreadsheets, CRMs and tasks through manual copying.
- Duplicates, missing information and assignments make the workflow fragile.
- An existing automation still needs constant intervention for errors and exceptions.
The outcome to agree
A pilot for an existing process: connected steps, clear responsibilities, visible errors and a manual fallback when needed.
What we deliver
- Map of the current workflow, rules, exceptions and baseline.
- Pilot integrations, fields, actions and approvals.
- Missing-data and duplicate checks, logs, alerts and recovery.
- Testing on authorised samples, documentation and training.
The first step
Business process automation and AI
The AI-ready Operations Sprint starts with a workflow map and a pilot. For example: incoming request, data preparation, human review, CRM update. We choose the process together.
Discuss this projectA clear scope
- The first sprint covers one process. Other departments, new integrations and CRM/ERP migrations are extensions.
- AI quality, technical costs and operational responsibilities are defined using samples and the specific case.
Price and timing are defined for your case after the brief. Deliverables, access, ownership, licences and support are explicit in the proposal.
How we get there
- 01
Observe real work and select a workflow with an owner.
- 02
Connect tools and use AI in the steps where it helps.
- 03
Test normal cases, exceptions, approvals and recovery before expanding.
What we need from you
- A process owner and the tools currently in use.
- Representative samples, rules and exceptions.
- Authorisable access and baseline data to compare outcomes.
Relevant experience
Integrations applied to work
Work on CGA Academy’s CRM includes integrations and AI automation. Vision also shows data and tools connected through APIs and MCP: it is an internal LuCz implementation.
Explore the experience →Before we start
No. A deterministic integration may be enough. We consider AI for interpretation, classification or preparing content when it helps the process.
Discuss this project
Price and timing are defined for your case after the brief. Deliverables, access, ownership, licences and support are explicit in the proposal.
Let’s discuss your project