Start a Value Discovery Sprint

RESULTS

The result is measured in business, not in technology.

Six engagements, anonymized by sector under NDA. Each one started with a baseline and ended with a number the client could check in their own reporting. No client names, no borrowed statistics.

Every case starts differently. They all end the same way: a metric that moves.

Financial services

Collections at scale, without growing the team at the same pace.

The need. The operation needed more coverage and more contact frequency without adding headcount in step with volume.

What we did. Process redesign, an AI agent on the contact sequence, automation of the administrative steps, and a supervised operation with exception gates.

100,000+
contacts managed per month
US$2.4M+
annualized economic value

Customer operations

Less waiting, more capacity on the same system.

The need. High interaction volume, high abandonment, and too much post-contact work per interaction.

What we did. Flow redesign, real-time assistance for agents, and automation of the administrative work after each contact.

9% → 0%
abandonment
−17%
average handle time
US$1.1M+
annual capacity recovered

Operations

From weeks of friction to an executable transition.

The need. A complex operation had to move between teams, processes and systems without stretching the change out.

What we did. Diagnosis, redesign, standardization, an execution plan, and governance of the change.

12 → 3
weeks of transition
75%
cycle reduction
US$850K+
value of time recovered

Beverages and consumer goods

From customer service to a sales engine.

The need. Turn each service interaction into a commercial opportunity and raise the average ticket.

What we did. Analytics integration, intelligent dialing, next best action, and connection to the order systems.

3x
contactability
1.5x
average ticket
+12%
sales

Supply chain

An order-to-delivery execution system.

The need. Exceptions across order intake, inventory, billing and claims were handled by hand across disconnected systems.

What we did. An agentic order-to-delivery layer over the ERP, TMS and WMS, with human checkpoints on pricing and credit exceptions.

−40%
exception-handling cost
3x
order processing speed

Read the playbook

Consumer goods distribution

A route-to-market tracking engine.

The need. Missed retailer orders and rep follow-up that depended on memory across an international distribution network.

What we did. Automated follow-ups, replenishment signals and a prioritization engine for the sales force.

−30%
missed retailer orders
2.5x
rep productivity

Read the playbook

A baseline before go-live. A number after.

Baseline first.

Before anything ships we measure the workflow as it runs today: hours, error rates, response times, cost per transaction. In your reporting, not ours.

Weekly after go-live.

The system reports against that baseline every week. The business case belongs to you, and so does the data behind it.

Method over statistic.

We publish results when they are ours to publish. When we cannot name the client, we show the measurement method instead of quoting a number without one.

One workflow. One owner. One measurable outcome.

The process was redesigned before any tool was chosen.

Eliminate, standardize, improve, automate, and only then agents. Automating a broken process runs the same errors faster.

Every automated action had a human gate and an audit trail.

Exception queues, approval screens and logs an examiner can read. Trust is the product.

Someone owned month four.

The team that built the workflow stayed to operate it, in the client's business hours, under the contract they signed.

Find where AI pays off first

A Value Discovery Sprint identifies your first workflow and the number behind it.

START A VALUE DISCOVERY SPRINT