AI that works in the workflow, not just in a demo.
Move from experimenting with generative AI to using it safely and consistently in daily work. KAITECH defines the target workflow, knowledge sources, answer quality, access control and operating rules, then introduces RAG and AI agents into the existing process. The focus is on reducing work for the people involved while keeping the solution practical and explainable.
Common Challenges
Have you encountered any of these common challenges?
- You want to adopt generative AI, but have not identified a workflow where its value can be measured
- Internal knowledge should be searchable, but answer grounding, accuracy and access control remain concerns
- A prototype is possible, yet the path to evaluation, improvement and ongoing operation is unclear
Our Approach
KAITECH first narrows the target workflow and users, defining what AI should handle and where human judgment remains necessary. We design the solution around knowledge retrieval with RAG, access control, usage history and evaluation, then test answer quality and operational effort through a focused use case. The results provide a practical basis for deciding what to improve and where to expand.
What We Deliver
- Select suitable workflows, assess risks and plan the rollout
- Design RAG using internal documents, FAQs and data
- Build AI chatbots, agents and workflow automation
- Integrate with existing web systems, APIs and access control
- Establish evaluation, logging, improvement cycles and operating guidance
In AI delivery, model selection must be considered alongside how the solution fits the workflow and who can access which information. KAITECH designs the process understanding, knowledge base, access model, evaluation and system integration needed to move from a PoC into practical production use.
This delivery approach is reflected in our related work. For an internal generative-AI chatbot supporting HR and labor enquiries, we designed a path to information that had been difficult to find and implemented it as a product intended for practical adoption on a short timeline. We connect discovery, focused validation, implementation and operational adoption rather than treating them as separate phases. Depending on the need, we combine RAG, LLM APIs, OpenAI API, Next.js, Node.js, vector search, access control and evaluation logs with the surrounding architecture, selecting technology around the service objective, maintainability and future expansion instead of using a stack for its own sake.
Well suited to internal enquiries, knowledge search, document support for sales, HR or legal teams, routine-work automation and AI proof-of-concepts. From the initial discussion, KAITECH can help you clarify the opportunity, requirements, delivery path and estimate for AI Agent & Generative AI Development.