Procedures are hard to observe at scale
Required steps and escalation paths live in manuals, systems, and training, while the actual conversations are reviewed only in small samples.
Put approved procedures inside every call review.
Evalyn® helps utility teams evaluate customer and operational conversations against their own procedures, apply human oversight, and turn recurring gaps into focused training.
Standards-led AI for high-consequence work, designed with utility operations experience on our team.
Your proceduresUsed as the evaluation source
Human oversightFor quality, flags, and appeals
Utility expertiseRepresented on the Evalyn team
01 / THE CONVERSATION
The procedure should survive the pressure of the call.
Customer needs, operational handoffs, escalation paths, and required language can converge in one conversation. Evalyn helps teams check the steps, surface patterns, and route sensitive calls for human review.
02 / WHAT GETS HIDDEN
High-consequence calls need more than a generic score.
Leaders need to know which step was missed, where the pattern appears, and when a conversation requires careful human judgment.
Context changes the right response
A keyword or generic sentiment score cannot explain whether the employee followed the correct process for the situation.
Findings stop at the dashboard
Recurring gaps are identified, but the work of explaining, training, and improving the evaluation still falls on internal teams.
03 / WHAT WE DO
A managed quality program around your procedures.
We combine structured analysis, human review, focused training, and practical AI workflow design.
Evaluate the steps that matter
Build scoring from approved procedures, required statements, verification steps, handoffs, and escalation paths instead of a generic model.
Route judgment to people
Surface sensitive or ambiguous conversations for careful review. Our team checks scoring quality and handles appeals with your standards in view.
Practice the missed decision
Turn recurring gaps into short instruction, reflection, and role practice grounded in the situations employees actually face.
Build the next useful workflow
Apply the same standards-led approach to operational information, review queues, and other manual processes where AI can support the team.
04 / HOW IT WORKS
Start with the procedure, then build the system.
- 01
Map the work
We learn the procedures, systems, call types, decision points, and human review boundaries.
- 02
Engineer the evaluation
Standards become criteria, AI instructions, expected evidence, flags, and post-processing rules.
- 03
Validate with people
Our team checks output quality, reviews flagged calls, responds to appeals, and refines the framework.
- 04
Train and extend
Findings become focused practice, and the same approach can support other information-heavy workflows.
05 / WHERE IT FITS
For customer and operational teams.
- Customer contact centers
- Gas and electric operations
- Water utilities
- Quality and training teams
- Program and process leaders
- Safety and compliance stakeholders
06 / QUESTIONS
Before you bring us a call.
Short, direct answers to what teams ask first. Anything else, bring it to the call.
01Does Evalyn decide what our procedures should be?+
No. Your approved procedures, subject-matter experts, and review boundaries define the standard. We turn that standard into an evaluation and operating workflow.
02How are sensitive conversations handled?+
The system can surface calls that warrant careful human attention. Review rules, escalation paths, and access depend on the workflow we design with your team.
03Can Evalyn support work beyond call scoring?+
Yes. We can scope AI-native tools for information-heavy operational processes. The right starting point depends on the task, systems, decision risk, and human review needs.
04Where should we begin?+
Start with one representative call or a specific workflow that consumes too much manual effort. We will review it and discuss a practical first scope.
A practical first step
Bring us one utility workflow.
Start with a call, a procedure, or an information-heavy process. We will review the work and show where a standards-led AI system could help.
Discuss your workflow
Human checked
Human checked