What challenges did GoTo Group face before AI implementation?

Existing database systems needed to support AI-ready capabilities such as semantic retrieval, in-database inference, and scalable high-throughput processing while reducing infrastructure complexity and latency for AI-driven workflows. Enterprises needed consistent access across structured, semi-structured, and unstructured data while keeping data within the local domain for privacy and compliance.

What was the impact of the AI solution?

GoTo Group said PolarDB's serverless scaling helped it reduce cloud resource usage by around 50% while handling peak traffic. Li Auto said PolarDB reduced technical complexity and accelerated the rollout and iteration of its AI initiatives. Atlas said PolarDB reduced infrastructure costs by 30% and enabled in-database AI pricing predictions while maintaining 97% booking success and 99% pricing accuracy.

Source

Alibaba

Alibaba Cloud PolarDB AI-ready database upgrades with in-database AI and model operators

Use case typeData platform modernizationUpdated Jan 26, 2026

Alibaba Cloud unveiled AI Lakebase architecture and upgrades for PolarDB to turn the database into an AI-ready data platform. The architecture unifies storage and analytics, supports multimodal data, and enables semantic retrieval and inference directly within the database. Customer deployments cited in the article include GoTo Group, Li Auto, and Atlas, each using PolarDB for AI-adjacent workflows such as lending, knowledge-base retrieval, AI coding, and real-time flight pricing predictions.

Organization: GoTo Group
Industry: Tech & Comms
Location: China
Published: January 2026

Reported outcomes

+99%

pricing accuracyQuality & accuracy

−50%cloud resource usage reduction−30%infrastructure cost reduction1,000,000,000 searchesdaily flight searches processed+97%booking success rate

Strategic outcomes

Speed & agilityAccelerated AI initiative rolloutRisk & complianceKept data within the local domainOther strategic outcomeEnabled in-database semantic retrieval and inference

Catalog median for quality & accuracy deployments: +90% across 281 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 2 of 2

1Data platform modernization
2Real-time analytics

Existing database systems needed to support AI-ready capabilities such as semantic retrieval, in-database inference, and scalable high-throughput processing while reducing infrastructure complexity and latency for AI-driven workflows.
Enterprises needed consistent access across structured, semi-structured, and unstructured data while keeping data within the local domain for privacy and compliance.

Alibaba Cloud upgraded PolarDB with AI Lakebase architecture, AI-driven cache acceleration, and proprietary in-database AI (Model-as-an-Operator).
The platform fuses KVCache, graph databases, and vector engines into a retrieval framework and supports semantic retrieval and inference directly inside the database.

Technologies

PolarDB AI Lakebase Tair KVCache Manager Model-as-an-Operator Graph database vector engine Global Database Network (GDN)

GoTo Group said PolarDB's serverless scaling helped it reduce cloud resource usage by around 50% while handling peak traffic.
Li Auto said PolarDB reduced technical complexity and accelerated the rollout and iteration of its AI initiatives.
Atlas said PolarDB reduced infrastructure costs by 30% and enabled in-database AI pricing predictions while maintaining 97% booking success and 99% pricing accuracy.

Architecture

AI Lakebase architecture unifies storage and analytics; AI-driven cache acceleration optimizes I/O and bandwidth; multimodal engine with in-database AI (Model-as-an-Operator) enables semantic retrieval and inference directly within the database; KVCache, graph databases, and vector engines form a high-performance retrieval framework; PolarDB Global Database Network (GDN) provides cross-region pricing consistency.

Sources & evidence1

Groundedness: 4/5Type: Blog PostPublished: Jan 26, 2026Publisher: Alibaba CloudEvidence: VendorConfidence: Medium

Primary source

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Customer evidence