Real-Time Calendar & Email Assistant
I have built a technical demonstration that connects an AI assistant with calendar, project, time-tracking, email and chat context. It explores how those sources can help an assistant prepare a response or understand availability.
This is a technical demo, rather than a product available to buy. Its purpose is to test the integration and the flow of information around an assistant.
Dual AI Engines for Speed & Efficiency
I have experimented with combining a local language model and the OpenAI API. The local model can handle smaller tasks or prepare context for a larger model, depending on the workflow.
Model choice, the data each step needs and the handling of sensitive information all need deliberate decisions. A local component does not make every connected part of a workflow private.
Beyond Standard Integrations
I explore caching, translation and contextual routing as well as chat interfaces. For example, translated content can be stored and refreshed when its source changes, rather than regenerated on every request.
The useful question is where automation reduces repeated work and where someone still needs to review the result.
AI Agents & Advanced Prompt Management
Reusable prompts and a structured context pipeline help make an integration easier to understand and refine. In ChatAI, each message draws on a fresh snapshot of relevant working context.
Supplying useful context can reduce guesswork, but the output still needs appropriate checks. I treat those limits as part of the application design.
Designing AI around the workflow
Useful automation starts with the information people already work with.
I connect interfaces, prompts and the context behind a task so an assistant can support a defined part of the process. The ChatAI prototype explores this through calendar, task and conversation context.
