Customer service
Intent, context, response, system action and escalation — handled as one coherent workflow.
AI × eCommerce × logistics
We design operational systems in which AI agents do the work, applications provide the framework, and people manage decisions, exceptions and quality.
We do not learn your industry from a brief. We understand the pace of operations, pressure of scale and cost of errors in eCommerce and logistics.
01 — A different perspective
Traditional automation repeats individual actions. We design the complete route to an outcome: understanding the case, gathering data, making a decision, taking action and handling exceptions.
02 — Services
From a responsible decision through the first production process to an environment that drives the entire operation.
Process Zero
Process assessment, working proof, autonomy matrix and a concrete implementation plan.
Explore the scope ↗AI Automation Sprint
The agent performs real work, uses company systems and involves people only for decisions and exceptions.
Explore the scope ↗AI Operations System
A purpose-built application connects people, agents, data and systems in one controlled way of working.
Explore the scope ↗Customer service · eCommerce · logistics · ongoing care
View all services03 — Our principle
The best process does not remove people from the equation. It moves them from performing every task to defining goals, setting rules, approving exceptions and developing the system.
04 — Where we create value
The greatest value is created where systems, teams and decisions meet — precisely where simple integrations stop being enough.
Intent, context, response, system action and escalation — handled as one coherent workflow.
Orders, catalogue, returns, claims and exceptions handled without manually switching between tools.
Detecting deviations, communicating and coordinating action before an issue becomes a crisis.
Documents, data, reports and repeatable decisions moving through a controlled, auditable process.
05 — Technology with context
For two decades we have built, developed and scaled technology for commerce and logistics. We know a process diagram is only the start — exceptions, data quality, user behaviour and accountability for the outcome are what matter.
Why Yuush06 — Proof in practice
PROECO GLOBAL LOGISTICSOne environment for quotes, loads, freight, communication, settlements and team oversight. See how logistics experience becomes a working product.
View case study07 — eCommerce at scale
EASTWOOD SOUND & VISIONLong-term development of specialist eCommerce for professional audio and video: thousands of products, a complex B2B/B2C offer and service that remains human.
View case study
LIVE ECOMMERCE / UK08 — Trust earned through delivery
Before we began teaching AI agents how to work through business processes, we spent years developing systems that daily sales and customer service depended on. Public reviews show what has not changed.
TrustScore and review count according to the public Yuush profile, observed on 31 July 2026. Values may change over time.
09 — See the process
Choose an event and see how an agent assembles context, uses tools, completes the work and gives a human only the decision that genuinely needs them.
It combines the carrier status, route and agreed SLA.
It checks alternatives, cost and impact on the recipient.
It sends an update, changes system records and sets monitoring.
Escalation appears only when the cost exceeds the agreed threshold.
10 — Straight answers
Questions worth asking before the first implementation — about autonomy, data, risk and accountability.
Only within boundaries we agree together. The level of autonomy depends on risk, model confidence and the value of the decision. Other cases go to a human with the full context.
We begin by classifying data and minimising access. We agree what information is needed, where it may be processed and how long it should be retained. The architecture follows your company requirements.
Usually not. Yuush agents and applications work as an operational layer across CRM, ERP, WMS, TMS, email and APIs. We modernise the workflow without unnecessary upheaval.
Before the pilot we define metrics: completion time, accuracy, escalation rate, cost per case and impact on the process outcome. Every action leaves an auditable history.
We design technical and operational controls: data validation, confidence thresholds, permission limits, approvals and reversible actions. An error should be detectable and contained.
Process Zero ends after 10 working days with a decision based on a prototype and real cases. A full pilot for one process usually takes a few more weeks, depending on integrations.
Our aim is the opposite of lock-in: we document the logic, architecture and policies, transfer knowledge and build tools your team can manage.
Next step
In our first conversation, we will identify the area with the greatest potential and test whether agentic automation makes business sense.
Book a process conversation