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Project context

Multi-Brand AI Customer Operations Platform

The customer-facing implementation of a shared AI platform for a multi-brand energy operation. One platform supports voice, chat, L2 ticket handling, debt-related flows, and sales conversations across 20+ brands without duplicating logic, knowledge, or governance.

Live productionMulti-brand energy operation2026

Client identity kept confidential

Modern glass facade reflecting layered red and blue planes — multi-brand surface
20+
Brands
Observed
5
Agent Roles
Observed
Voice + Chat + Tickets
Channels
Observed

Evidence

Observed in the customer-facing implementation. The figures describe live platform scope across brands, roles and channels rather than a productivity claim.

The challenge

The solution

Technology stack

LangGraphpgvectorElevenLabsMulti-Agent RoutingCRM / ERP Integration

The result

The result is one customer-operations platform instead of separate bots per brand or channel. Voice, chat, L2 support, debt-related flows, and sales conversations can share routing, knowledge, references, and governance while still behaving differently where needed.

That reduces rollout friction, keeps maintenance realistic, and makes the platform easier to expand as the operation grows. It also reflects the truth of the implementation better: this is not one support agent, but a reusable agent layer for a multi-brand operation.

Next step

Want to explore where this could land first in your operation?

Start with one concrete process. In the AI Opportunity Scan we assess where AI adds value and what the best first route looks like.

Multi-Brand AI Customer Operations Platform Case Study | Laava