CUSTOMER RESULTS

The result matters.
So does the context.

See the work before Briano, what changed, and what each reported result actually measures.

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Three different operations. Three specific implementations.

Published customer evidence
GPI Insurance customer story
50-60%Time saved on the manual processing stage

ClaimPilot · Insurance

GPI Insurance

01

Before

Teams manually read photographs, receipts, invoices and medical forms, then entered the information into internal systems. This stage could take 15-20 minutes per claim.

02

What changed

ClaimPilot extracts document information into a consistent structure, validates it against existing data, and delivers it to GPI’s systems through an API.

03

Reported result

Early operational results indicate approximately 50-60% of the time previously spent on the manual processing stage can be saved.

Measurement context

This measures the manual processing stage, not the entire claim lifecycle. Implementation and business-impact measurement are ongoing.

More about this result

The story reports approximately one month for implementation, integration and testing in this deployment. This is not a standard rollout commitment.

Source published October 20, 2026. View original source ↗

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Spega Medical customer story
65%Reported solution rate

CX Agent · Medical e-commerce

Spega Medical

01

Before

Growing e-commerce traffic increased questions about products, availability, delivery and order status. Support specialists also needed time for complex or medically sensitive enquiries.

02

What changed

A support agent uses structured service knowledge to answer routine enquiries and hands complex or sensitive cases to people.

03

Reported result

The published customer story reports a 65% solution rate and a first response time below three seconds.

Measurement context

These are results from this implementation. The published story does not specify the measurement window, sample size or full definition of solution rate.

More about this result

Medical advice and sensitive interactions remain with the appropriate human specialists. The implementation concerns e-commerce service support.

Source published June 6, 2025. View original source ↗

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Crystalbet customer story
45-50%Requests resolved without a human

“Customers get answers right away, while our teams can focus on complex cases that truly require human attention.”

Juna TatarishviliCrystalbet

CX Agent · Gaming

Crystalbet

01

Before

Support demand could rise several times above usual levels during sporting events and campaigns, creating queues around routine account and service questions.

02

What changed

The agent answers common questions from a structured knowledge base, gives the first response, and transfers cases requiring people with a summary of the latest request.

03

Reported result

In the most recent observed month described in the published story, approximately 45-50% of incoming chat requests were resolved end to end without human involvement.

Measurement context

The period is the latest month described in the source, not a rolling live result. Waiting-time and satisfaction improvements were qualitative while dashboards were being finalized.

More about this result

The story also reports first-response coverage in 100% of conversations. First-response coverage and autonomous resolution are different measures.

Source published September 17, 2025. View original source ↗

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MAKE YOUR OWN RESULT MEANINGFUL

Agree the measure before the pilot.

Define the baseline, sample, measurement window and quality checks. Track the complete outcome, including the cases that still need people.

Plan a pilot

HELPFUL BY DESIGN

A credible business case
starts with your baseline.

Use the customer stories as context, then test the opportunity in your own workflow.

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