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MIP · AI PRODUCT LAUNCH 2026

The NextBegins Here

MirrorShip Intelligence Platform AI Product Launch

Explore MIP’s product direction, architecture, and practical applications—and see how it supports Agents working with enterprise data.

View Agenda
DATE & TIME
October 20, 2026 | 14:00 (UTC+8)
ONLINE LIVESTREAM
Online Livestream | LinkedIn
PRODUCT · ARCHITECTURE · PRACTICE
Product / Architecture / Practice

About

Join us online on October 20 for the launch of MIP, the MirrorShip Intelligence Platform. We’ll introduce its architecture and core capabilities, with product demonstrations showing how enterprise data and business definitions become part of an Agent’s analytical process.

MIP is MirrorShip’s real-time unified AI data platform. Built on a unified data engine and business semantics, it connects enterprise data, knowledge, and task-specific context, giving Agents a foundation for working with enterprise data.

Enterprise dataBusiness semanticsTask context

Help AI Understand Enterprise Data

Data lives in databases, business definitions in people’s minds, and knowledge across documents. MIP brings them together so Agents can analyze enterprise data within defined boundaries, with traceable execution.

Agenda

5 SESSIONS
0114:00–14:10

From StarRocks to MIP: The Evolution of Data Infrastructure in the AI Era

Explore the thinking behind the evolution from StarRocks to MIP, the data infrastructure needs of the AI era, and MIP’s product direction.

Vincent Sun
CEO, MirrorShip
0214:10–14:35

MirrorShip’s AI-Era Product Strategy

Get a high-level view of MIP’s architecture and design principles, including how data, business semantics, and context work together.

Andy Chen
CTO, MirrorShip
0314:35–15:10

MIP - The Real-Time Unified AI Data Platform

Explore MIP’s product scope, three-layer architecture, and use cases, followed by a hands-on demo of a lightweight application.

Yingting Dong
Head of Product, MirrorShip
0415:10–15:30

Multimodal Data Lake Retrieval with StarRocks and Paimon

Learn how hybrid vector and full-text search supports training-data selection and hard-example mining in large-model training and autonomous driving.

Kang Zhou
Kang Zhou
Head of the Open-Source OLAP Engine Team, Alibaba Cloud
StarRocks TSC Member
0515:30–15:50

From Serving People to Serving Agents

Explore practical methods for implementing MIP, from data integration and semantic modeling to AI application deployment.

Bao Li
Bao Li
Big Data Architect, Guangzhou Haijie Technology

All times are in Beijing Time (UTC+8).

MIP Product Launch Replay

Explore the product direction, architecture, and practical applications. Select a session to watch.

Sessions

5 SESSIONS
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MIP · PRODUCT LAUNCH

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