Glimp

Introduction to Glimp

Glimp is a desktop application designed to provide real-time, undetectable AI assistance during live professional conversations such as job interviews, sales calls, and presentations. It operates as a local, low-footprint co-pilot that processes audio and screen content in real time to generate contextual responses, feedback, and analysis—without requiring cloud-based processing for core functionality. Target users include job seekers (especially technical and non-technical candidates), sales professionals, product managers, data scientists, and other professionals who engage in high-stakes verbal interactions.

The tool emphasizes privacy, stealth, and usability: all context files (e.g., resumes, job descriptions) are parsed locally; audio transcription occurs in real time with no persistent storage; and the interface is engineered to remain invisible during screen sharing, task switching, and system monitoring. Glimp currently supports Windows, with macOS support under development.

Key Takeaways

• Real-time audio capture of both microphone and system audio using low-latency local processing
• Ghost Mode: a transparent, floating overlay invisible to screen-sharing platforms (Zoom, Google Meet, Microsoft Teams), task managers, alt-tab switchers, and the macOS dock
• Multimodal screen analysis: visual content (e.g., coding challenges, diagrams, slides) is analyzed in real time via local or hybrid processing
• Keyboard-only control: repositioning, resizing, and activation require no mouse interaction and leave no visual cues (e.g., cursor changes)
• Post-interview performance reports with actionable insights, including sentiment analysis and delivery suggestions
• Local-first architecture: context parsing, transcription, and core AI inference occur on-device where possible; end-to-end encryption applies to any required cloud processing
• Customizable UI: adjustable background opacity, text size, color scheme, and fill opacity to match user environments
• Resume and job description upload for personalized answer generation and contextual grounding

How Glimp Works

Glimp operates through a five-step workflow. First, users load context by uploading resumes, job descriptions, or other relevant documents to build a local knowledge base. Second, they configure audio input by enabling system audio loopback—capturing both their voice and the interviewer’s or caller’s audio without external hardware. Third, they activate Ghost Mode to launch the transparent overlay, which begins transcribing questions in real time and generating AI-suggested answers visible only to the user. Fourth, when visual content appears (e.g., a coding problem on screen), users trigger Screen Snap to initiate multimodal analysis. Finally, after the session ends, Glimp generates an automated post-call report summarizing performance metrics, conversational patterns, and improvement opportunities.

The application runs as a privileged desktop process with rendering techniques that isolate its UI layer from standard screen-capture APIs. It does not appear in Windows Task Manager, macOS Activity Monitor, or application switchers. All keyboard shortcuts are configurable and operate without triggering window focus changes or visual feedback. Audio processing uses on-device models where feasible; when cloud processing is required (e.g., for complex multimodal inference), data is encrypted in transit and not stored.

Core Benefits and Applications

Glimp supports diverse professional use cases across technical and non-technical domains. In technical interviews, it provides real-time coding assistance—including algorithm suggestions, system design frameworks, and debugging guidance—by analyzing code displayed on-screen or transcribed speech. For sales and marketing roles, it delivers objection-handling prompts, behavioral interview frameworks, and case study analysis tailored to conversation context. In presentations and client meetings, it offers live sentiment analysis and delivery refinements (e.g., pacing, clarity, confidence cues). The tool also enables accessible preparation for candidates facing anxiety or knowledge gaps, functioning as a responsive, private rehearsal partner. Its local-first design ensures compliance with strict data governance requirements, making it suitable for regulated industries where cloud data submission is restricted.