Deep Insight Technology makes its debut at NRF 2026 Asia-Pacific Retail Show, partnering with Indonesia’s leading retail technology provider to usher in a new AI‑driven supply chain paradigm.


Release time:

2026-06-05

Deep Insight Technology was invited to participate in the exhibitor‑led creative‑sharing session, taking the stage alongside Indivara Group, Indonesia’s leading retail‑technology conglomerate. Their presentation, titled “From Automation to Autonomy: A Retail Supply Chain’s AI Transformation at Scale,” drew significant attention.

From June 2 to 4, 2026, the NRF Retail’s Big Show Asia Pacific, the global retail industry’s annual flagship event, will be held in Singapore. This year’s conference is expected to bring together more than 13,000 industry professionals from over 70 countries.

Deep Insight Technology was invited to participate in the exhibitor‑led creative‑sharing session, taking the stage alongside Indivara Group, Indonesia’s leading retail‑technology conglomerate, under the presentation theme— “From Automation to Autonomy: A Retail Supply Chain's AI Transformation at Scale” (From Automation to Autonomy: The AI‑Driven Scaling Transformation of Retail Supply Chains) has drawn significant attention.

The following is a transcript of this sharing session.

01.

A problem that has hit many retailers hard.

The presentation began with an industry dilemma: We’ve automated everything that can be automated—so why is the supply chain still falling short?

Three sets of data directly highlight the crux of the issue: many retailers are operating… 5 or more Fragmented supply chain systems; despite the comprehensive presence of WMS, TMS, and OMS, 72% of exception handling They still rely on telephone and instant messaging; the gains from automation have not only reached their peak but are also declining gradually. Deep Insight Technology has dubbed this phenomenon the “Supply Chain Efficiency Paradox.”

02.

The Real Challenges Facing Traditional Retail in Indonesia

Indivara Group CTO Antonius Kho

Indivara Group CTO Antonius Kho presented the specific implications of this paradox in emerging markets.

Traditional retail in Indonesia accounts for of the country’s total retail outlets. 98.5% , with an annual transaction volume exceeding 90 billion US dollars However, it has long remained outside the digital ecosystem. The Bersama platform, under Indivara Group, was created precisely for this purpose: by enabling retail outlets to place orders online via a mobile app and connecting them with wholesalers for same-day delivery, it helps traditional retailers integrate into the modern fast-moving consumer goods supply chain.

As of now, Bersama has expanded its reach across Indonesia. More than 50 cities , with over active outlets 32,600 companies , active wholesaler 472 companies As the company scales, the complexity of supply chain management grows in tandem—this is precisely why Bersama turned to Deep Insight Technology.

03.

When Retail Networks Meet AI-Driven Supply Chains

Philip Leong, Head of International Business at Deep Insight Technology, took the stage to unveil the end-to-end supply chain cloud platform jointly developed by both parties.

Philip Leong, Head of International Business at Deep Insight Technology

The solution leverages Bersama’s retail network as its collaborative foundation, with implementation support provided by Deep Insight Technology, covering… Order Management (WHO), Warehouse Operations (WMS/WES), Transportation Dispatching (TMS/YMS) seamlessly integrates the entire end-to-end supply chain, from order placement to last-mile delivery, while leveraging warehouse agents, transportation agents, and a control tower to maximize autonomous decision-making across the entire value chain.

This joint solution has also served as a real-world validation of Deep Insight Technology’s AI capabilities in complex, emerging markets.

04.

Where exactly has the paradigm shifted?

With real-world scenarios as a foundation, Deep Insight Technology further elucidates the fundamental differences underlying technological transformation.

The boundaries of traditional automation are clear: executing predefined tasks, optimizing individual systems, responding passively, and relying on manual handling of exceptions.

AI Agents, by contrast, are entirely different: they are goal‑driven, enable cross‑system collaboration, proactively address anomalies in real time, and continuously self‑optimize. Deep Insight Technology has distilled this closed loop into: Perception → Judgment → Action → Self-healing 。

In terms of deployment, Deep Insight Technology offers two approaches— Human–robot collaboration model Enable agents to assist human decision-making while retaining approval authority. Multi-Agent Autonomous Orchestration Mode The primary agent decomposes tasks, while the subordinate agents collaborate to execute them, making this approach well-suited for scenarios that prioritize high levels of automation. These two components are not mutually exclusive; rather, they should be selected flexibly based on the maturity of the business process.

05.

Professional agent group, covering all scenarios across the supply chain.

Underpinning these capabilities is the DI.AI platform, which Deep Insight Technology has developed over 22 years and refined through serving more than 600 clients. The platform currently hosts dozens of specialized AI agents, covering five major domains: warehousing, transportation, freight forwarding, shipping, and general‑purpose applications. The presentation highlighted six agents designed to address the most common pain points in the warehousing and transportation scenarios:

Warehousing scenario

Restocking Agent

Automatically generate purchase orders and replenishment plans for buffering, enabling… Labor savings of 20–35% Inventory lead time reduced by 50%;

Inbound Planning Agent

Automatically parse the arrival time window, intelligently schedule dock resources, and push real-time anomaly alerts—expected. Inbound waiting time reduced by 50% , Platform utilization has increased by approximately 60%;

ABC Diagnostic Agent

Dynamically update SKU value classifications, automatically identify risks of slow-moving and overstocked inventory, and generate inventory optimization recommendations with a single click. Inventory turnover is expected to improve by approximately 30%. 。

Transportation scenario

Intelligent Loading Agent

Automatically generates loading plans and issues outbound delivery orders, reducing the onboarding time for new employees from two weeks to approximately two days. Shipping efficiency can be improved by 30–50%. ;

Shipping Cost Diagnostic Agent

Real-time detection of cost anomalies and automatic generation of root-cause reports, reducing response time from 24 hours to real time. Exceptional losses decreased by approximately 80%. ;

Rate Negotiation Agent

Automatically conduct fare negotiations and contract updates across systems, significantly shortening the bidding cycle. Expected improvement in reconciliation efficiency of 95% 。

* Actual performance data may vary depending on the business scenario.

06.

China’s supply-chain AI is already gaining traction overseas.

At the Deep Insight Technology booth, NRF 2026 Asia-Pacific Retail Show, Singapore

This appearance on the NRF Asia-Pacific stage marks a product showcase for Deep Insight and serves as proof to the global retail community that China’s supply-chain AI is already operating effectively in the capillaries of overseas markets.

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AI gives us not just visibility, but decision‑making power. Turning AI agents into true core members of supply chain teams—that’s what Deep Insight Technology is doing, and it’s also our new way of delivering value to customers worldwide.

Deep Insight Technology is an AI‑agent‑driven provider of intelligent supply chain solutions. Our product suite—built on the DI.AI platform, including WMS, TMS, CargoNova, and the Control Tower—has been deployed at scale across warehousing, transportation, freight forwarding, and shipping, delivering measurable business value to customers worldwide.

Tag:

Retail,AIAgent,Warehousing and Transportation System,Supply chain