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Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.

Klarwatt

Front-office resolution layer for EU energy retailers that answers consumption and billing contacts from the customer's own metering data,…

A front-office resolution layer for EU energy retailers that answers consumption and billing contacts from the customer's own metering data, and provably hands the contact to a person whenever unbundling rules, vulnerability protections, or metering-data purpose limits require one.

DemoDeployment-Ready FoundationfazeZERO VerifiedProprietaryEnergy & Utilities

Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v1

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Configuration + implementation engagement

Problem

Inbound "why is my bill higher" contacts at a residential supplier with 0.5–5M meter points in a rolled-out smart metering market — the highest-volume, lowest-margin contact class, and the one a knowledge-base chatbot cannot answer because the answer lives in half-hourly data, a tariff change, and a corrected estimated read.

Outcome

A deployment-ready foundation that teams can configure into production.

Who uses it

  • Operations Analyst
  • Solution Architect

Key capabilities

  • Core workflow

    AI-assistedIncluded

    Primary operating workflow for this foundation.

  • Document intelligence

    AI-assistedIncluded

    Extract and ground decisions from operating documents.

Typical workflow

Primary operating flow

Trigger: An operator starts the primary use case

  1. Task

    Stage 1: Capture inputs

    Operator

  2. AI-assisted

    Stage 2: Assist with draft

    System

  3. Human checkpoint

    Stage 3: Human approval

    Approver

Task Automated AI-assisted Human checkpoint Decision

About this foundation

Regulated contact automation for energy retail. Generic customer-service AI treats an energy supplier as a call centre with a knowledge base; Klarwatt treats it as a licensed entity whose every automated utterance is constrained by the role it is speaking in, the lawful purpose of the data it used, and the protected status of the person it is speaking to — and makes the pilot-to-scale decision a measured event rather than a board-level hunch.

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