AI Agent Builder
EXDREAM ORIGINAL PRODUCTAI AGENT BUILDER
An AI agent builder that combines semi-custom agent modules tailored to each company’s operations with multiple LLMs, enabling flexible, visual configuration.
Rather than another isolated AI tool, we are designing one foundation for workflows, knowledge, human judgment, and multiple specialist agents. It will also support EXDREAM advisory and forward-deployed projects while enabling enterprises to keep evolving their own system.
PRODUCT VISION
AI AGENT BUILDER
An AI agent builder that combines semi-custom agent modules tailored to each company’s operations with multiple LLMs, enabling flexible, visual configuration.
MULTI-AGENT KNOWLEDGE & TRAINING
Structure proprietary company data and expert know-how as RAG-ready knowledge. By combining multiple specialist AI agents, we develop an advanced conversational system: multi-agent RAG.
INDUSTRY AI APPLICATIONS
Develop industry-specific AI agents that use documents, drawings, specifications, and operational data from construction, manufacturing, and logistics to support schedules, work planning, and technical decisions. Combined with consulting support, they aim to create value in daily operations.
COMMON PLATFORM
Define work in natural language, structure knowledge, and deploy multiple AI agents around human judgment. Add industry- and company-specific modules as requirements evolve.
Make objectives, inputs, outputs, tasks, decisions, and approval rules explicit through dialogue.
Transform documents, expert decisions, and procedures into knowledge that RAG systems can use.
Coordinate distinct agents for retrieval, analysis, education, planning, and operational support.
Preserve human judgment and accountability, then improve knowledge and agents from real usage.
DEVELOPMENT MODEL
Capabilities under development will also be used in EXDREAM advisory and transformation projects. Field requirements and pilot results will continuously improve the reusable product foundation.
Define management and workflow requirements, then identify the knowledge, decisions, and data involved.
Prototype dedicated agents in the enterprise and validate human-AI roles, quality, and operations.
Turn shared capabilities into a platform with reusable industry and enterprise modules.