Bring agentic workflows to your organization.
We connect your existing business systems with information inside and outside your organization, enabling AI to identify work and carry it through execution, verification, and reporting.
Agentic operations are a way of working in which AI handles tasks from understanding the situation through planning, execution, and verification, in line with the goals and rules of the business.
AI responds to requests and alerts, and also identifies work that needs to be done as information changes inside and outside the organization.It consults existing business systems and documents, asking the people responsible for any missing information.Within the approved scope, it updates systems and contacts the relevant people, then checks and reports the results.
People set the goals and scope of the work, make important decisions, approve actions, and handle exceptions.When a decision is needed, AI checks with a person and resumes the work once that decision has been made.
We design what AI handles and where people decide around the needs of each workflow.
Coordinating deliveries, resolving conflicting information, responding to security risks, and handling after-hours inquiries.These four examples show the work AI handles and where people make decisions.
Order and stock checks
When a customer asks to change a delivery date or split a shipment, AI checks orders, stock, and expected arrivals. It asks colleagues for missing information and prepares a reply and arrangements. After approval, it applies the changes, verifies them, and reports back.
Procedures and FAQs
AI checks whether meeting decisions, procedures, and customer guidance agree. It confirms official decisions and exceptions with the people responsible and prepares revisions. Following approval, it updates documents, shares them with the relevant people, and verifies that the changes are reflected.
System operations
AI compares external security information with your internal system configuration. It assesses whether action is needed and prepares an update and verification plan. It follows the approved plan, checks that systems operate correctly, updates configuration records, and reports the results.
Customer support
Review an inquiry received after hours against response rules and earlier cases. Prepare a reply within the permitted scope and hand uncertain cases to staff with the findings.
Our team has built platforms for developing business systems, core systems for large enterprises, and open-source libraries and SDKs. We understand data structures and business rules, connecting existing systems with AI.
From UX designers to engineers, everyone on our team works with AI. We handle the process from understanding day-to-day work through design, development, and ongoing management and operations. Using Helmr as a shared runtime lets us focus on your specific workflows and rules.
We have worked in startups where daily decisions and development directly shape business results. In line with your goals, we examine time spent, the burden on people, missed tasks, and progress on work that previously went untouched. We use those findings to improve both workflows and systems.
We learn how work gets done today and agree on the first workflow and budget together.We introduce AI within a defined scope, observe the changes in practice, and expand the work it takes on.
We discuss your challenges, systems, and the information you need.
We agree on the roles of AI and people, the budget, and the changes to evaluate.
We introduce it within a limited scope and check how work progresses and how it feels to use.
We assess the burden on people and changes in the work, then consider improvements and a wider scope.
Kijitra refines the environment AI works in through our day-to-day operations, the products we build and run, and client projects.We turn human corrections and decisions into procedures, approval criteria, and verification methods that inform the next task.
We use these systems daily in our operations and products, identifying and improving the work and decisions that still fall to people.
We connect existing business systems and information sources so people and AI can work together.
(Japanese)
We build and operate AI workflows that investigate, fix, and verify issues in native app maintenance.
(Japanese)Improvements from all three areas
feed our shared foundation
We combine deep knowledge of business systems with experience in UX and development to build systems that change how work gets done.
CEO
Taiki worked as a UX designer for four years while studying in Australia and Taiwan. After moving to Tokyo in 2014, he supported the growth of digital services, primarily at startups, through UI and UX design as well as building teams and processes for continuous product improvement. After helping launch Querier, a platform for building business systems, he began supporting businesses through Kijitra in July 2026.
COO
Akane spent three years designing UI and UX for mobile apps and web services at a design agency. She has worked alongside clients to build services, interviewing them about their goals and workflows and clarifying the features they need. Her experience spans requirements definition, UI design, prototyping, and design system development. She also coordinates specifications with engineers and proposes improvements after implementation, translating client needs into tools they can put to use.
Engineer
Masato helped launch Querier, a platform for building business systems. As a full-stack engineer at startups, he has worked from user and stakeholder interviews through requirements definition, interface design, and implementation. He maps out data entry and review steps, translating workflows into interfaces and system behavior. Drawing on experience in both design and development, he builds business systems that are easy to use in everyday work.
Technology Partner
While supporting companies as an engineer, Akatsuki saw how much development time went into admin interfaces. In 2020, he developed Querier, a low-code platform that connects to databases and APIs. He is now developing Helmr, infrastructure for running AI agents. By building in human approvals and the ability to pause and resume tasks, he designs and implements the foundations that let AI carry out real work.
