Ovopark Technology Co., Ltd

Ovopark Technology Co., Ltd OVOPARK is committed to making retail chains smarter, faster, and more efficient.

OVOPARK AI solution has empowered 5,000+ brands and 500,000+ stores worldwide, serving well-known companies across retail, food service, fashion, etc.

A brand is set to launch a new promotional campaign on Monday. Head office has issued the same instructions to 200 store...
24/08/2026

A brand is set to launch a new promotional campaign on Monday. Head office has issued the same instructions to 200 stores:

Update the displays, replace the price tags, clear the promotional areas, and train staff.

However, the actual implementation in the stores may vary considerably.

One shop has arranged the displays correctly. Another has placed items in the wrong locations. Yet another has only completed half the tasks. And one has simply stated that the work has been carried out.

For retailers with multiple stores, the gap between head office plans and what customers actually see in-store is a key factor affecting profits

1. Completion ≠ Correct Ex*****on
2. Manual inspections can only capture a snapshot in time
3. By the time issues are discovered, the opportunity has already been missed

If a promotional campaign is executed incorrectly for three days, the losses incurred during that period cannot be recovered afterwards. This is why in-store ex*****on requires not only manual supervision and management, but also AI verification.

OVOPARK solves this problem by utilising AI cameras, compatible CCTV systems and AI algorithm inspection capabilities to identify specific visual SOP irregularities. It then feeds this evidence back to head office, allowing teams to focus on the stores that truly require attention.

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The report reveals that, according to a global survey, 96% of food and grocery retailers have now adopted self-checkout ...
19/08/2026

The report reveals that, according to a global survey, 96% of food and grocery retailers have now adopted self-checkout systems. In certain supermarket formats, the report states that as many as 80% of transactions are completed via self-checkout. With such widespread adoption, losses at the checkout stage are set to become a routine part of day-to-day store operations. A single instance of an item being missed at the checkout may involve:

staff intervention, POS data and customer behaviour, among other factors. At the same time, in order to trace these incidents, the IT department requires video evidence, operations teams need to oversee corrective measures, and store managers require action plans.

Consequently, the next phase of retail loss prevention will no longer be limited to simply installing more CCTV cameras, but will involve correlating transaction data, in-store incidents and operational responses. The most powerful loss prevention system may ultimately resemble an operating system rather than a security system.

OVOPARK also operates on this principle, integrating in-store CCTV recordings, AI analysis, POS transactions and SOP processes, thereby making loss prevention an integral part of day-to-day store management rather than a separate audit process.

Retailers often lack actionable data. A modern shop is already capable of generating information through POS systems, CC...
13/08/2026

Retailers often lack actionable data. A modern shop is already capable of generating information through POS systems, CCTV cameras, stock management systems, footfall counters and staff reports. Consider what happens on a daily level, for example

The POS detects an unusual refund, while the checkout transaction has been matched.
The stock management system alerts staff to out-of-stock items.
The entrance CCTV records the peak-time footfall for the day.

It appears that each system fulfils its own function. However, as they operate independently, someone is still required to correlate this information and decide on the next course of action. This is precisely where retail AI comes into its own.

OVOPARK’s AI retail solution utilises a single platform to build the following workflow:

Detection → Analysis → Alerts → Rectification → Verification

From detecting stock shortages on the shelves, to notifying shop staff, to the shop manager overseeing the restocking task, and finally the area manager verifying that the shelves have been restocked. This is the difference between a conventional shop and a smart shop. Separate systems do not necessarily lead to better management. A one-stop service, however, can guide the right decisions

Generally speaking, an empty shelf does not always mean there is no stock. The problem is that the goods are in the back...
11/08/2026

Generally speaking, an empty shelf does not always mean there is no stock. The problem is that the goods are in the back storage, and no one has noticed the gap on the shelf in time. For retailers with multiple outlets, managing shelf stock levels becomes difficult for the following reasons:

1. Staff are unable to continuously check every shelf.
A shelf may remain empty for 20, 40 or even 60 minutes before anyone notices.

2. There is a discrepancy between stock data and the actual situation on the shelves.
The system may show that stock is available, whilst customers see empty shelves.

3. Head office supervision is not timely.
By the time manual checks are carried out or store reports are received, a significant amount of potential revenue has been lost.

This reflects issues with internal ex*****on and visibility within the store. For retailers, the question is no longer simply:

“Do we have this SKU?” But rather:

“Can customers actually buy this SKU right now?”

Ovopark’s AI store solution helps clients achieve visualised, actionable and efficient store management through a single platform.

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According to KPMG’s [2026 Retail AI Report], 64% of executives in the consumer goods and retail sectors regard AI as a t...
06/08/2026

According to KPMG’s [2026 Retail AI Report], 64% of executives in the consumer goods and retail sectors regard AI as a top investment priority.

However, many retailers, particularly individual outlets, are currently deriving only minimal benefits. The difference usually does not lie in whether or not they have adopted AI. The key lies in whether AI has been integrated into actual SOPs. Individuals and businesses have begun using AI tools to perform functions such as gathering information and analysing documents or data, which stems from integrating AI with day-to-day workflows.

OVOPARK’s AI store solution similarly connects the following elements:

AI cameras / Existing cameras→ AI NVR → POS integration→ AI algorithms → Alerts and actions

Management no longer needs to review live feeds or verify POS records. Instead, they can access a results dashboard that clearly shows what has occurred and which areas require attention.

AI is already widely used in ensuring compliance with standard operating procedures in retail outlets. The next step is to utilise AI to optimise SOPs and enhance management, thereby boosting conversion rates for the outlets.

Some shop managers aren’t keen on dashboards or complex reports. What they need are answers, just as their staff would p...
31/07/2026

Some shop managers aren’t keen on dashboards or complex reports. What they need are answers, just as their staff would provide them. CamClaw is designed to be an AI assistant.

Instead of constantly sifting through CCTV footage, reports and spreadsheets, shop managers can simply ask operational questions. For example:

‘Hey, CamClaw. Can you check the hygiene in the kitchen?’

‘Hey, CamClaw. Which shelves need out of stock?’

“Hey, CamClaw. What counter anomalies have been detected?”

CamClaw integrates AI cameras, AI NVR, operational rules and shop data to help managers understand the situation, identify anomalies and create To-do tasks. Its aim is simple, to reduce tedious searching and provide actionable insights straight away.

How do you think about this function? Is it helpful if you use Camclaw in daily operation? Leave your comments here!

Have you hear about workflow? Today, tools like ChatGPT, Claude Code and Gemini are used to build AI workflows that col...
29/07/2026

Have you hear about workflow? Today, tools like ChatGPT, Claude Code and Gemini are used to build AI workflows that collect information, analyse data, surface issues, and generate reports or tasks automatically.

The key value is continuous support across a workflow. This reduces manual work and improves operational visibility. The same applies to retail.

OVOPARK’s AI store solution connects AI Cameras, AI NVR, POS data and store systems into one operational workflow. It can detect traffic, queues, shelf issues, and ex*****on problems, link them with POS data, and compare them with store SOPs. When exceptions occur, it sends alerts, generates reports, and supports follow-up actions across stores.

Instead of switching between cameras, reports and records, managers get a view of what is happening and what needs attention.

AI workflows are reshaping digital work. OVOPARK brings this to physical retail operations. The goal is not more cost, but better visibility and reasonable decisions.

Let's back to the question last week. Two stores. Similar products. Similar customer groups. Yet one store performs cons...
28/07/2026

Let's back to the question last week. Two stores. Similar products. Similar customer groups. Yet one store performs consistently better. The difference is rarely the location. It is usually hidden inside daily operations. In OVOPARK opinion, operational gaps that quietly separate high-performing stores from average ones:

1. Shelf management based on data rather than experience.
2. Staff scheduling that follows customer traffic instead of fixed shifts.
3. Daily store visibility instead of weekly reports.
4. Continuous ex*****on tracking instead of scheduled inspections.

These differences are small on a single day. Across hundreds of stores, they will be magnified. Modern retail is no longer only about choosing the right location. It is about managing every location more intelligently.

OVOPARK supports this transformation through AI Cameras, AI NVR, customer insight and multi-store operational visibility. Do you think this point of view is correct? Leave you comments and let's talk about this!

AI is developing faster than most business processes can adapt. Our CEO Mr @ also expressed the same view a few weeks ag...
22/07/2026

AI is developing faster than most business processes can adapt. Our CEO Mr @ also expressed the same view a few weeks ago.

ChatGPT is changing how teams research, analyse information and complete everyday knowledge work. Claude Code shows how AI can participate directly in software development, reading codebases, modifying files and running tests. Gemini is becoming increasingly connected with business information, productivity tools and daily workflows. The important change is not the name of the model. It is the movement from asking AI a question to allowing AI to participate in real work. This shift is especially important for retail. Retail operations contain thousands of repetitive, observable and time-sensitive decisions:

1. Reviewing whether stores follow operating standards.
2. Connecting POS transactions with checkout video.
3. Identifying long queues, shelf gaps and staffing exceptions.
4. Turning store data into alerts, tasks and follow-up actions.
5. Comparing ex*****on across hundreds of locations.

Waiting for AI to become “finished” is not a realistic strategy. AI tools will continue to develop, and their applications will continue to expand.

Retailers do not need to apply AI everywhere at once. A more practical approach is to select one clear operational problem, test AI in a controlled scenario, verify the result and gradually connect it with existing cameras, POS systems and store workflows. Accepting AI is a mindset. Applying AI is an operational capability.

The retailers that build this capability earlier will learn faster—not only about technology, but also about their own stores. Which retail workflow should move from manual judgement to AI assistance first?

Do you meet or face the similar thing beside you? Two stores open in the same neighbourhood. They sell similar products,...
20/07/2026

Do you meet or face the similar thing beside you? Two stores open in the same neighbourhood. They sell similar products, serve similar customers and operate under similar market conditions. Yet their daily turnover can be completely different.

One store maintains stable shelf availability, reasonable queues and consistent service. The other frequently experiences empty shelves, understaffed peak hours, delayed reports and inconsistent ex*****on. The difference is not always the location. It is often the management system behind the store. This gap usually appears in four areas:

1. Staffing based on experience, rather than actual customer flow.
2. Restocking after complaints, rather than identifying shelf gaps earlier.
3. Reviewing weekly reports, rather than receiving daily operational signals.
4. Manual inspections, rather than continuous ex*****on tracking.

Traditional store management records what has already happened. Modern AI- powered management helps teams understand what is happening now, and what needs attention next. Over time, this difference becomes visible at every shelf, checkout and shift. Store modernization does not mean replacing people with technology. It means giving retail teams better data, faster feedback and more consistent management tools.

OVOPARK supports this transition through AI Cameras, AI NVRs and centralized multi-store management. In two similar community stores, which operational difference usually appears first? Let's talk about this in the comments!

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