Domain Knowledge Agents
Turn your private knowledge and expertise into domain knowledge agents that can answer questions, support workflows, and apply domain expertise.
Answer with Knowledge. Act with Skills.
Turn your private knowledge and expertise into domain knowledge agents that can answer questions, support workflows, and apply domain expertise.
Answer with Knowledge. Act with Skills.
Why not just use ChatGPT directly?
AI tools like ChatGPT already have tremendous knowledge, language and reasoning capabilities, especially when you provide the right context, documents, or information together with your question or task.
But as private knowledge grows and workflows become more specialized, ad hoc prompting becomes difficult to manage and scale. Real-world domains often need trusted knowledge retrieval, reusable expertise, structured reasoning, and more efficient ways to work with large and evolving knowledge bases.
Answer questions about guest services, local transportation, and operational rules.
Review reports, identify potential risks, and support safety-related decisions.
Remember stories, personal notes, creative ideas, and experiences accumulated over time.
i80agent supports trusted retrieval, reusable skills, or a combination of both.
For known questions, the agent retrieves grounded answers directly from your structured knowledge base, sometimes without calling an LLM.
Example: “How to use Wifi?”
For complex requests, the agent applies reusable expert skills for analysis, workflows, and decision support.
Example: “Apply the Medical Monitor Review skill to this adverse event listing.”
i80agent supports different agent patterns. Some requests go directly to trusted knowledge. Others require agent skills guided by domain expertise. More advanced use cases can coordinate multiple agents through an orchestrator.
Retrieval and skills capabilities can work independently or together. More advanced systems may coordinate multiple agents through an orchestrator.
i80agent is designed for domains where the most important knowledge lives inside private documents, workflows, business processes, and domain expertise.
Cooking stories, memories, journals, creative processes, research notes, and personal archives.
Hotel guest assistants, restaurant knowledge systems, service operations, and internal SOP access.
Document review, risk analysis, workflow guidance, and operational support.
Internal support agents, HR onboarding, product documentation, and team knowledge systems.
What started as a personal experiment has grown into a broader exploration of how domain knowledge agents can be built, refined, and eventually made accessible to others.
I am building this in my spare time alongside a regular job, so progress comes in waves and moves more slowly than I would like. But life, cooking, travel and curiosity are also part of the journey.
Built the first working knowledge agent based on my personal cooking stories.
Extended the same architecture to a real-world hotel assistant use case.
Rebuilt the Alex Cooking agent into the Spontaneous Cooking by Alex set-menu dinner experience.
Continued improving retrieval quality, answer structure, embeddings, and practical usability.
Paused active development to rethink the foundation as AI tools and capabilities evolved faster than expected.
Began rebuilding i80agent using ChatGPT, OpenAI Codex, Claude Chat, and Claude Code, with a stronger focus on Retrieval Agents, Workflow Agents, and Orchestrator Agents.
Expanded i80agent from knowledge retrieval into expert task execution.
The goal is to evolve i80agent into a generic platform for building domain knowledge agents that can retrieve knowledge, apply expert workflows, and coordinate real tasks.
It started with a simple realization: LLMs are powerful, but they do not know your personal or business knowledge.
What began with cooking stories and personal memory evolved into a broader vision: domain knowledge agents, reusable workflows, and real-world expertise.
How It All Begani80agent is still evolving.
Many of the ideas behind i80agent are being explored through real-world projects and guided implementations. The goal is not just to solve individual problems, but to discover reusable patterns that can eventually evolve into a broader agent platform.
If you have real-world use cases, are exploring domain-specific AI, or want to turn expert workflows into reusable agent skills, I’d love to connect and exchange ideas.
Get in Touch