Build a macOS Live-Call Copilot Connected to ChatGPT and My Existing Work Context

Willing to pay more for the right outcome. I want a personal AI assistant that listens during live calls and suggests what I should say next, using the relevant knowledge from my existing ChatGPT work conversations. The main value is context. I do not want a generic transcription tool or sales coach that knows nothing about my work. WHAT I WANT TO EXPERIENCE Before a call, I select the relevant work/client context. During the call, the app hears both the other participant through computer audio and me through my microphone—even when I use headphones. It follows the conversation and displays concise, natural responses I can say aloud. For example, if a client asks about a process, agreement, or previous discussion, the assistant should use the relevant background already documented in my work conversations, identify what is known, and help me respond without inventing facts. Afterward, I can review a summary and new information, then bring approved learnings back into the appropriate ChatGPT work conversation or context collection. CHATGPT INTEGRATION — A CORE REQUIREMENT I already use ChatGPT extensively for work. I want this tool to connect to that workflow rather than become a separate knowledge silo that I have to train from scratch. The solution should: Use my existing ChatGPT subscription allowance where an official, supported integration permits it. Explain clearly if any part instead requires separately billed API access or a transcription service. Bring in the full relevant context from a work conversation I select, including important facts, prior decisions, terminology, responsibilities, and supporting documents I explicitly provide. Preserve access to the selected source material rather than relying only on a tiny, manually written summary. Retrieve the relevant information during the call without mixing unrelated employers or clients. Support an explicit update process when the source context changes. Produce a reviewable post-call summary and proposed context updates. “Full context” means the selected material is available to the assistant when relevant. It does not mean every word must be sent to the model with every request. IMPORTANT: Do not assume signing in with ChatGPT grants access to my chat history, Projects, files, or memory. Please explain your proposed approach. If direct access to selected conversations is not officially supported, propose a practical alternative such as importing an export, uploading selected files, or maintaining a synchronized local context collection through supported methods. Similarly, if direct writeback to ChatGPT is unavailable, a well-formatted review packet that I can bring into the correct conversation is acceptable for the first version. No unofficial session-cookie reuse, credential scraping, or unsupported ChatGPT endpoints. LIVE-CALL REQUIREMENTS Native or otherwise dependable macOS application. Capture system audio and microphone audio. Work with headphones. Accurately follow both sides of a conversation. Automatically show a brief suggested response after the other participant speaks. Include a useful follow-up question when appropriate. Clearly distinguish verified context from statements made during the call. Avoid fabricated approvals, commitments, deadlines, or answers. Keep suggestions readable without constantly replacing them. Provide visible listening status and an immediate Stop button. Report useful errors instead of appearing to listen while nothing works. FIRST-VERSION SCOPE Keep the initial delivery focused: One user and one Mac. One selected business-context profile. English first. Simple, functional interface. Reliable context import and live suggestions. Reviewable post-call export. No CRM integration, team accounts, mobile app, or commercial distribution. The context structure should allow additional separate work profiles later. TECHNICAL ENVIRONMENT Mac mini M4 with 16 GB RAM. Last verified macOS version: 15.5. Existing experimental Swift app and Python backend available as optional reference. You may build from scratch. You are not required to repair or reuse the prototype. Choose an implementation you can explain, test, and deliver. Avoid heavy local models unless you first establish that they are appropriate for the machine and obtain approval. WHAT YOU WILL OWN I want someone to handle the complete implementation: Confirm the feasible ChatGPT authentication and context-import approach. Build the audio, transcription, context-retrieval, and suggestion workflow. Handle installation, signing, and permissions appropriately. Test the components with known audio before asking me to rehearse. Demonstrate the complete workflow on my target setup. Deliver the source code, runnable application, and clear instructions. I will provide selected business context, complete account sign-in and permission approvals, and participate in final testing. ACCEPTANCE TEST We will agree on practical accuracy and latency targets before starting. Final delivery should include a 15-minute fictional call demonstrating that: Both participants are captured while I use headphones. Important wording is preserved, including negation, names, dates, and approval status. Suggestions use facts from an imported sample work conversation, including information from earlier parts of that conversation. The assistant acknowledges missing information rather than guessing. Unrelated context is not included. Suggestions appear automatically with measured latency. Silence does not stop the session or create repeated failures. Stop ends capture and prevents new automatic requests. The application can be closed and reopened using the supplied instructions. A post-call summary and proposed context updates can be reviewed and exported.