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Case studies

Sales prioritisation: Energies France equips its 30 sales reps with a custom AI platform

The AI Sisters Lab designed, built and runs a platform that scores every prospect and tells sales reps who to call first

Custom development · 4 months from assessment to production
Maquette mobile de la plateforme de priorisation d’Energies France : prospects notés sur 100 et lots d’appels du jourRetour du directeur juridique d’Energies France, avec 30 commerciaux équipés et 4 mois de l’évaluation à la production
“

We did not expect to go this far.

Sahil Aouni, Legal Director, Energies France

Energies France asked the AI Sisters Lab to design a sales prioritisation platform for its 30 sales reps.

Four months passed between assessment and go-live. The code belongs to the client.

The goal: every call goes to the prospect who deserves it.

Knowing who to call in a prospect file

Thirty sales reps were calling through a prospect file without knowing which ones deserved their time. Records were incomplete and the best opportunities got lost in the crowd.

The challenge for AI Sisters: build a tool that applies the company’s sales rules, without touching the existing system.

Incomplete records

There was not enough information to judge a prospect before calling.

House rules

No standard tool could have applied Energies France’s own sales rules.

No wasted licence

An off-the-shelf tool meant a recurring licence, months of setup and features never used.

An untouched source system

The existing system had to remain the reference, with no changes at all.

What if it were you?

An off-the-shelf tool does not fit your rules?

We design and build with you the AI tool that applies them.

Discuss my project

Our custom AI development for Energies France

A platform designed, built and run by AI Sisters. Delivered in increments: the client approves each building block before committing to the next.

01

Assessment and scoping

Analysis of the sales rules, the available data and the source system.

02

Read-only synchronisation

The platform reads data from the existing system, which remains the reference and is never modified.

03

Scoring and call batches

Each prospect gets a score out of 100, a plain-language explanation and a recommended action. Call batches are generated twice a day.

04

Calibration and operation

The model is compared with the sales reps’ own assessment, then adjusted. AI Sisters hosts and maintains the platform.

Les six étapes de la plateforme Energies France, de l’évaluation des règles commerciales à la production
What if it were you?

An AI use case to put into production?

Discover our support for building AI agents, from audit to adoption.

Build my AI agents

AI use cases for a sales team

The platform supports the sales reps’ daily work, from choosing calls to following up on records.

Bento de la plateforme Energies France : 30 commerciaux, 2 lots d’appels par jour et une livraison par incréments en 4 mois

Prioritise calls

→ A score out of 100 for every prospect

→ A plain-language explanation of the score

→ A recommended action for every record

→ Call batches generated twice a day

Make the scoring reliable

→ The company’s sales rules built into the model

→ A model calibrated on the sales reps’ assessment

→ Read-only synchronisation with the source system

Run the platform

→ Hosting and maintenance by AI Sisters

→ Code owned by the client

Results of the platform at Energies France

The platform is in production. The client approved each increment before committing to the next.

30

sales reps using the platform

4 months

from assessment to go-live

2

call batches generated every day

/100

a score per prospect, with its explanation

What if it were you?

A sales team calling blind?

Let’s talk about what custom scoring could change for them.

Got it. An AI Sisters expert will email you to plan your AI training.

Your email didn't go through. Check the address, or write to us at contact@aisisters.ai.

An expert will reply to scope your AI training, with no commitment.

Client
Energies France
Sector
Energy
About the client
Energy sector company with a team of 30 sales reps.
Teams supported
Sales team, 30 people
Format
Custom development delivered in increments, then hosting and maintenance
Period
4 months from assessment to production
Tools
Custom web platform, code owned by the client
Train your teams in AI

A programme built around your roles and your tools, pre-audit included.

Got it. An AI Sisters expert will email you to plan your AI training.

Your email didn't go through. Check the address, or write to us at contact@aisisters.ai.

An expert will reply to scope your AI training, with no commitment.

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They got their teams to adopt AI: Accor, La Poste, Samsung, JCDecaux, Vinci, Engie, Ipsen, Havas, BPCE, CMA CGM, TV5Monde, Webedia, Google 4.9/5
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