Rakuten Launches AI Shopping Assistant in Japan

Rakuten, Japan's largest e-commerce platform, has officially launched an AI-powered personal shopping assistant designed to revolutionize online retail for its 100+ million domestic users. The new tool, integrated directly into Rakuten Ichiba — the company's flagship marketplace — uses the firm's proprietary large language model to deliver hyper-personalized product recommendations, conversational search, and real-time deal discovery.

The move positions Rakuten as a direct competitor to Amazon's AI shopping initiatives and signals a broader trend of e-commerce giants racing to embed generative AI into every stage of the consumer journey.

Key Facts at a Glance

• What: Rakuten launches a conversational AI shopping assistant embedded in its Rakuten Ichiba marketplace
• Technology: Built on Rakuten's proprietary LLM, fine-tuned with billions of product listings and purchase history data
• Market: Initially available to all Japanese-language users across mobile and desktop
• Scale: Rakuten Ichiba hosts over 380 million product listings from 57,000+ merchants
• Investment: Part of Rakuten's reported $1 billion AI investment strategy through 2025
• Competition: Follows Amazon's launch of Rufus and Google's AI-enhanced Shopping experience

Rakuten Bets Big on Proprietary AI for Retail

Rakuten's decision to build its shopping assistant on a proprietary large language model rather than relying on third-party solutions like OpenAI's GPT-4 or Google's Gemini is a deliberate strategic choice. The company has been investing heavily in its in-house AI capabilities since 2023, when it first unveiled plans for Rakuten AI, a family of models trained specifically on Japanese-language data.

The shopping assistant understands natural language queries in Japanese, including colloquial expressions, regional dialects, and complex product specifications. Unlike keyword-based search, users can now type queries like 'I need a lightweight waterproof jacket for hiking in Hokkaido next month' and receive curated results filtered by weather appropriateness, price range, and user reviews.

This approach gives Rakuten a significant advantage in its home market. Japanese consumers have long complained that Western-built AI tools struggle with the nuances of Japanese language and cultural context — a gap Rakuten is explicitly targeting.

How the AI Assistant Actually Works

The assistant operates as a conversational interface layered on top of Rakuten Ichiba's existing search and recommendation infrastructure. When a user initiates a shopping session, the AI engages in a multi-turn dialogue to understand preferences, constraints, and intent.

Here's what the assistant can do:

• Conversational product discovery: Users describe what they want in natural language, and the AI narrows results through follow-up questions
• Cross-category bundling: The assistant suggests complementary products across different categories (e.g., pairing a camera with a compatible memory card and carrying case)
• Price tracking and alerts: It monitors price fluctuations and notifies users when items drop below their target price
• Review summarization: The AI condenses thousands of user reviews into concise pros-and-cons summaries
• Seasonal and contextual awareness: Recommendations factor in upcoming holidays, weather patterns, and regional events

The system draws on Rakuten's massive first-party dataset, which includes over 20 years of transaction history, browsing patterns, and loyalty program data from Rakuten Super Points — one of the largest consumer reward ecosystems in Asia.

Amazon's Rufus vs. Rakuten's New Assistant

The launch inevitably draws comparisons to Amazon's Rufus, the AI shopping assistant that rolled out to U.S. customers in early 2024. Both tools share a similar vision — replacing static search bars with dynamic, conversational commerce — but their approaches differ in meaningful ways.

Amazon's Rufus is built on the company's broader Bedrock AI infrastructure and trained on Amazon's product catalog, customer reviews, and web data. It excels at answering general product questions and making broad recommendations across Amazon's global catalog.

Rakuten's assistant, by contrast, is laser-focused on the Japanese market. It understands the 'omotenashi' (hospitality) culture that Japanese consumers expect, providing more detailed explanations, politeness levels, and contextual suggestions than its Western counterparts. The assistant also integrates with Rakuten's ecosystem of services — including Rakuten Mobile, Rakuten Travel, and Rakuten Card — creating cross-platform recommendation opportunities that Amazon cannot easily replicate in Japan.

Industry analysts note that this localization advantage could prove decisive. Japan's e-commerce market is projected to reach $240 billion by 2026, and cultural fit often matters more than raw technological capability in consumer-facing AI.

The Technical Architecture Behind the Scenes

Rakuten has been relatively transparent about the technical foundations of its AI strategy. The company's Rakuten AI division, led by CTO Ting Cai, has developed a family of models ranging from 7 billion to 70 billion parameters, with the shopping assistant reportedly running on a mid-range model optimized for inference speed.

Key technical details include:

• Training data: The model was pre-trained on a large Japanese-language corpus and then fine-tuned with Rakuten's proprietary e-commerce data
• Retrieval-Augmented Generation (RAG): The system uses RAG to pull real-time product information, ensuring recommendations reflect current inventory and pricing
• Latency targets: Rakuten aims for sub-2-second response times, even during peak traffic events like Rakuten Super Sale
• Privacy architecture: User data is processed in compliance with Japan's APPI (Act on Protection of Personal Information), with on-device processing for sensitive queries

The RAG approach is particularly notable. Rather than relying solely on the LLM's training data — which can become stale — the system queries Rakuten's live product database in real time. This means the assistant always has access to current pricing, stock levels, and new product listings.

Why This Matters for the Global E-Commerce AI Race

Rakuten's launch is more than a regional product update — it represents a significant data point in the global race to AI-ify e-commerce. Every major retail platform is now building or deploying conversational AI tools, and the strategies are diverging in interesting ways.

Amazon and Google are pursuing broad, multi-market approaches powered by general-purpose LLMs. Chinese giants like Alibaba and JD.com have deployed AI shopping assistants powered by their own models, including Alibaba's Tongyi Qianwen. Shopify has integrated AI across its merchant tools, while eBay uses AI for listing optimization and pricing.

Rakuten's strategy stands out because it combines a proprietary model with deep ecosystem integration. The company operates financial services, telecommunications, streaming, and travel businesses — all feeding data into a unified customer profile. This 'Rakuten Ecosystem' approach gives the AI assistant context that pure-play retailers simply cannot match.

For Western companies watching this space, the lesson is clear: the future of AI shopping is not just about the model — it's about the data moat and ecosystem integration surrounding it.

What This Means for Developers and Businesses

Merchants on Rakuten Ichiba will need to adapt their product listings to work effectively with the AI assistant. Rakuten has released updated guidelines encouraging sellers to include detailed product attributes, structured data, and high-quality descriptions that the LLM can parse effectively.

For AI developers, the launch validates the approach of building domain-specific, language-specific models rather than defaulting to English-centric general-purpose solutions. The Japanese AI market remains underserved by Western model providers, creating opportunities for specialized solutions.

Investors should note that Rakuten's AI push comes at a critical time for the company. After years of heavy losses from its mobile network buildout, Rakuten is under pressure to demonstrate that its technology investments can drive revenue growth. A successful AI shopping assistant could boost conversion rates, increase average order values, and reduce customer acquisition costs — all metrics Wall Street and Tokyo markets are watching closely.

Looking Ahead: Expansion Plans and Market Impact

Rakuten has indicated that the shopping assistant is just the first phase of a broader AI rollout. The company plans to expand the assistant's capabilities to include voice-based shopping, visual search (where users upload photos to find similar products), and proactive notifications that anticipate purchase needs based on past behavior.

International expansion is also on the roadmap. Rakuten operates e-commerce platforms in France, Germany, and several other markets. Adapting the AI assistant for these regions would require additional language training and cultural calibration, but the underlying architecture is designed to be modular.

The timeline for these expansions has not been publicly confirmed, but industry sources suggest voice and visual search features could arrive by Q1 2026, with European market pilots potentially following by mid-2026.

As generative AI continues to reshape online retail, Rakuten's launch underscores a fundamental shift: the search bar is dying. In its place, conversational AI assistants are becoming the primary interface between consumers and the products they want. For the $6 trillion global e-commerce market, this transformation is only beginning.