Headquarter.ai was invited to join AWS’s “From Regional to Global: Amazon Innovation Strategy Launch.”
During the morning session, we presented our AI Workflow platform and customer use cases. With a visual interface to rapidly build customized AI workflows—fully deployed within the customer’s own AWS account—we ensure data sovereignty and security. More than just model integration, Headquarter.ai enables LLMs to become a true execution engine in enterprise workflows.
At the AWS Summit, Headquarter.ai showcased real-world deployments of AI Workflows, sharing proven case studies and partnering with leading experts who understand the unique needs of both public and private sectors. Over 1,000 attendees visited us onsite to explore practical applications of AI Workflow.
On the same day, at the AWS Partner Summit, we delivered a keynote session: “Generative AI Business Opportunities: From Demand Insights to Revenue Transformation.”
Partnering with the Public Sector to Realize AI Governance
At the 2025 Digital Government Summit, we connected directly with public sector teams to explore the future of AI in governance. Onsite, we presented our recent success story—the AI Tax Assistant solution—demonstrating how Agentic Workflow technology enables AI to be deployed effectively, improving both service efficiency and regulatory compliance.
We were encouraged to see strong interest from many government agencies, along with exciting ideas for future collaboration.
Headquarter.ai partnered with the Ministry of Finance Information Center and the Kaohsiung National Taxation Bureau to transform complex tax Q&A workflows into an AI Agentic Workflow.
Previously, tax officers needed 1–2 days to review citizen petitions, search relevant tax regulations, and draft formal responses. With the AI Tax Assistant, this process now takes just 5 minutes to generate a preliminary case analysis.
Importantly, the system does not replace professional tax officers. Instead, it works collaboratively with experts—accelerating administrative tasks while leaving final judgment and governance to human professionals.
Build a truly practical, enterprise-grade AI question-answering system, from LLM and knowledge integration to customized business needs, all in one step. This video provides a complete, step-by-step tutorial on Long Form QA. Using a "medical knowledge question-answering system" as an example, we demonstrate how to progress from basic LLM applications to advanced AI agentic workflows that integrate proprietary knowledge and provide contextually referenced and categorized answers. This isn't just an LLM; it's a comprehensive process for building a question-answering platform that can be controlled, managed, and evolved by the enterprise.