Platform brings together high-performance analytics, shared business definitions, and data agents to support traceable enterprise analysis HONG KONG, Oct. 20, 2026 /PRNewswire/ -- <a href="https://mirrorship.ai/en/" target="_blank" rel="nofollow" style="color: #0000FF">MirrorShip</a> today announced the launch of MirrorShip Intelligence Platform (MIP), an enterprise AI data platform that connects high-performance analytics, business semantics, and data agents. Building on MirrorShip's real-time analytics foundation, MIP enables organizations to analyze data using defined business metrics, governed access, and traceable query execution. As enterprises adopt AI agents, generating a query is only part of the challenge. Reliable analysis also requires a clear understanding of how metrics are calculated, how business data is related, and which information a user is authorized to access. At the launch, MirrorShip CEO Vincent Sun emphasized that enterprise AI must be grounded in real data, consistent business definitions, and trusted data access. Rather than pursuing unrestricted question answering, MIP focuses on verifiable analysis within defined business domains, supported by human feedback and ongoing refinement. A shared platform for data, business context, and agents MIP comprises three layers―MirrorData, MirrorMind, and MirrorPilot―with MirrorControl providing governance, security, and operational management across the platform. MirrorData provides a unified data foundation for reporting, applications, and agent workloads. It combines MirrorBase, a real-time analytics engine built primarily on StarRocks, with MirrorLake for open lakehouse storage. The platform supports queries across native tables and lake tables, including Paimon, Iceberg, and Hive, and combines structured filtering, full-text search, and vector search for further analysis. MirrorMind provides an enterprise semantic layer. Semantic Views define metrics, dimensions, relationships, and calculation rules, while Knowledge Context supplies supporting business rules, terminology, documentation, and analytical methods. MirrorPilot provides a data agent and an environment for running and delivering agent-based analytics. Users can ask questions through a conversational interface or access the same capabilities through APIs integrated into existing BI tools and business applications. MirrorControl supports access control, resource isolation, and auditing and observability of agent analysis. Demonstrations connect platform capabilities to business tasks During the launch, MIP Product Lead Yingting Dong demonstrated image-based retrieval, semantic metric calculation, and retail business analysis. A simulated after-sales workflow combined image similarity, text descriptions, and date filters in a single SQL query. A separate comparison showed how a Semantic View guided an agent to the correct budget metric, rather than summing unrelated amount fields from a raw table. Ecosystem perspectives on retrieval and enterprise implementation Ecosystem partners, including Alibaba Cloud, offered further perspectives on retrieval and enterprise AI adoption, complementing the event's focus on MIP. With MIP, MirrorShip is extending its analytics foundation to help enterprises put existing data, business knowledge, and analytical methods to work in AI applications. The company's approach focuses on defined use cases, governed access, and results that users can inspect and validate. <a href="https://mirrorship.ai/en/" target="_blank" rel="nofollow" style="color: #0000FF">About MirrorShip</a> MirrorShip connects real-time data, enterprise context, and governed agent execution so organizations can turn data and knowledge assets into verifiable, traceable, and controllable business intelligence.

MirrorShip Launches MIP, an Enterprise AI Data Platform

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