Not another chatbot. A lifecycle reasoning and orchestration layer.
This demonstrator imagines ALVA as the connective intelligence between customer communication, engineering models, enterprise systems, quality evidence and the installed machine.
Six capabilities around governed action
RFQs, emails, P&IDs, specifications, service reports and operating narratives become structured context.
Pull controlled data from CRM, PLM, ERP, QMS, document repositories and asset history.
Use sizing logic, cost models, configuration constraints, risk rules and lessons learned.
Evaluate consequences across technical design, BOM, margin, schedule, test and service.
Create review packs, change requests, sourcing scenarios, test records or service cases.
Recommendations cite their source evidence, assumptions, confidence and required approval.
Autonomy stops where accountability begins
| Agent may | Human gate required |
|---|---|
| Extract & classify requirements | Accept contractual scope |
| Run approved sizing rules | Release safety-critical design |
| Prepare sourcing alternatives | Approve supplier change |
| Assemble FAT evidence | Sign formal acceptance |
| Recommend service action | Authorize intervention |
“What changed, what does it affect, and what should we do?”
The agent can answer across functions because the customer request, requirements, models, BOM, cost baseline, production evidence and verification plan share a common project thread.