DATA
Connect and understand enterprise information.
About FST Network
FST is an AI data specialist. We began with enterprise data technology; today Anytime Data uses AI to build enterprise super knowledge bases, while AKai turns that knowledge into professional applications for real work.
Connect and understand enterprise information.
Build the enterprise super knowledge base.
Activate knowledge through AKai applications.
Company journey
FST began with enterprise data software, expanded through investment, cloud and innovation ecosystems, and now advances industrialized AI through AKai and the Anytime Data Enterprise Data Knowledge Service.
Started with enterprise data software and cross-system data technology.
Supported by the National Development Fund, H&Q Asia Pacific, Red Building Capital and AVA.
Built partnerships across AWS, Microsoft Azure and Google Cloud; joined Japan FINOLAB incubation and the Epoch Foundation accelerator.
Selected among Taiwan's Top 100 Startups.
Serving enterprises across Japan, Taiwan and Southeast Asia with data knowledge and AI applications.
Founded in 2018, FST grew from cross-system data software into an AI data company serving enterprises across Japan, Taiwan and Southeast Asia. The same experience that taught us how data moves through ERP, documents, databases and operational systems now lets us automate how enterprises understand and use it.
We do not build a manual data factory. Anytime Data uses AI to connect, interpret, classify, pre-validate, anticipate and preprocess enterprise information, continuously forming a governed super knowledge base. Data Lineage, metadata, business logic and proven operating experience become knowledge that AI can actually use.
AKai brings that knowledge to the foreground. Its A2A architecture coordinates specialized agents through SOP Keeper, Insight Keeper and Knowledge Keeper, so users can adopt professional AI inside familiar work—not through another isolated experiment.
Our goal is simple: let enterprise experience survive team changes, reduce repeated preparation and turn every successful implementation into a faster, lower-cost starting point for the next one.