Noesis and an anonymised omnichannel retailer: POS test automation case analysed
Verdict: what is checkable
The evidence grade (this site's label for how a case is sourced: primary with client or press confirmation, secondary when vendor-hosted only.) is secondary: the only source is the vendor's own page; of 6 metrics, 0 are verifiable yes, 0 partial and 6 no. [ev-1639]
Client profile as published
- Client
a major Portuguese Retailer
(the vendor's description; the vendor does not name the client)- Segment
- Enterprise omnichannel
- Region
- Portugal
- Channels
- stores
- Size indicators
- none given
The client description and size indicators are quoted from the source; segment, region and channels are this site's classification. [ev-1639]
Systems in scope
- POS (point of sale: the till software and hardware that rings up store sales, takes card payments and prints receipts.): named in The Challenge section of the vendor PDF (the store area (POS)) and in the Solution section
- Integrations (Kafka): named in The Challenge section of the vendor PDF (the integration area (Kafka)) and in the Solution section
Where the source names each system is quoted or summarised from the case page. [ev-1639]
Problem as stated
The retailer wanted shorter implementation times, and its regression battery took roughly 5 days to run across the Kafka integration layer and the store POS. Noesis set out to cut that execution time, remove the effort of maintaining the automated tests, and validate core business processes such as stock management and promotional actions. [ev-1639]
reduce the execution time of the regression battery(quoted from the source)
Approach
- Testing types
- automation, functional and api (main scope: automation)
- Team shape
- not stated
- Duration
- not stated
- Engagement model
- not stated
- Tooling named in the source
- none named
Metrics claimed
| Metric | Value | Unit | Claimed by | Verifiable | Evidence |
|---|---|---|---|---|---|
| regression battery execution time before the work | roughly 5 days | days | vendor | no | ev-1640 |
| regression cycle time saving (listed under Goals) | approximately 70 | % | vendor | no | ev-1641 |
| FTE capacity released per sprint | 0.5 | FTE per sprint | vendor | no | ev-1642 |
| automated test cases | 400+ | tests | vendor | no | ev-1643 |
| end-to-end flows executed daily | 600+ | E2E flows per day | vendor | no | ev-1644 |
| flows validated by the daily regression battery | +60 | flows | vendor | no | ev-1645 |
What the case does not say
- Measurement method.
- Duration over which the metric held.
- Team size on both sides.
- Cost.
- What was out of scope.
- Whether the client is still a client.
- Date of the work.
Reading notes for a buyer
This case speaks to the scenario “POS rollout across stores” and feeds dimension D4 (Test automation evidence) of the methodology. A question to put to Noesis:
Was the cycle time saving reached or does it remain a goal, and how many flows does the daily battery validate? [ev-1639]
Source and verification
- Source
- Optimized Time-to-Market with AI Based Automated Functional Testing
- Published
- not dated by the vendor
- Verified
- 2026-10-30
- Evidence grade
- secondary
- Corroborating sources
- none found
| Id | Claim | Source | Class | Grade | Published | Verified |
|---|---|---|---|---|---|---|
| ev-1639 | Optimized Time-to-Market with AI Based Automated Functional Testing | Optimized Time-to-Market with AI Based Automated Functional Testing | vendor-case-study | secondary | 2026-10-30 | |
| ev-1640 | Working with this leading Retailer, we faced the challenge to reduce the execution time of the regression battery (that took roughly 5 days to execute) in both the integration area (Kafka) and in the store area (POS). | Optimized Time-to-Market with AI Based Automated Functional Testing (Use Case PDF) | vendor-case-study | secondary | 2026-10-30 | |
| ev-1641 | Time-to-Market Optimization: saving up approximately 70% of cycle time during regression testing. | Optimized Time-to-Market with AI Based Automated Functional Testing (Use Case PDF) | vendor-case-study | secondary | 2026-10-30 | |
| ev-1642 | 0.5 FTE capacity released in each sprint | Optimized Time-to-Market with AI Based Automated Functional Testing (Use Case PDF) | vendor-case-study | secondary | 2026-10-30 | |
| ev-1643 | 400+ Automated test cases within 1 IA mechanism | Optimized Time-to-Market with AI Based Automated Functional Testing (Use Case PDF) | vendor-case-study | secondary | 2026-10-30 | |
| ev-1644 | 600+ E2E flows executed daily | Optimized Time-to-Market with AI Based Automated Functional Testing (Use Case PDF) | vendor-case-study | secondary | 2026-10-30 | |
| ev-1645 | The daily execution of the regression battery, with validation of +60 flows, frees up 0.5 FTE capacity in each sprint, available to perform other tasks. | Optimized Time-to-Market with AI Based Automated Functional Testing (Use Case PDF) | vendor-case-study | secondary | 2026-10-30 |
Vendor profile: Noesis.
Positions on this page are computed from the methodology published at /methodology/ and from the evidence records linked on this page. Case study figures are the vendor's or the client's claims as published at the linked source; the "verifiable" column states what this site could check. The site does not recommend vendors, does not accept paid placement and does not publish rates. Last computed: 2026-11-03.
Published by the editor of retailqavendors.com. Last reviewed .