Presence

The description states:

• Presence is a "local-first, Windows-first AI interview avatar studio".
• It allows an owner to prepare an approved profile from resume, LinkedIn facts, personal context, speaking style, boundaries, portrait, and disclosure recording.
• The studio supports owner-present practice with OpenAI Realtime, shows a minimized grounding trace, and routes disclosed output through OBS or Windows Media Foundation virtual-camera path.
• It is described as a tool for practicing interviews, providing review, scoring, suggestions, and guidance on posture, discussion, and presentation.

Inference The product appears to be a desktop application that uses AI to simulate interview scenarios, with strong emphasis on user consent and control over data usage.

The description states:

• The idea came from the frustration of not feeling prepared during interviews.
• Existing AI assistants are seen as problematic because they can invent experience, hide AI involvement, retain sensitive material, or act without owner control.
• Presence explores a "different model": a disclosed AI avatar that represents only one consenting owner, only from approved professional knowledge, while the owner remains present and able to stop it immediately.

Inference The positioning is centered on privacy, transparency, and user agency in AI interactions — a contrast to current AI tools that may obscure their role or misuse data. The claim evolution seems to be moving from a hackathon prototype toward a more mature product with broader platform support.

The description states:

• The tool is for people preparing for job interviews.
• It helps users practice interview skills, improve posture and presentation, and get feedback on how they express experience using methods like STAR methodology.

Inference The primary customer segment appears to be job seekers or professionals in transition who are looking for structured interview preparation tools.

Not evidenced.

The description does not mention any pricing model, monetization strategy, or business model.

The description states:

• Built with React, TypeScript, Vite, Express, Electron, OpenAI Realtime over WebRTC, LiveKit, Tavus, and Windows Media Foundation helpers.
• Sensitive owner content is stored in an AES-256-GCM encrypted local vault protected by the Windows current-user context.
• Native process-loopback and virtual-camera components keep media in memory and expose narrow, fixed operations to the Electron renderer.
• Codex with GPT-5.6 was used for implementation, testing, and documentation.

Inference The technical stack suggests a desktop application with strong emphasis on local processing, encryption, and secure handling of sensitive data. The use of multiple technologies indicates a complex integration effort.

Not evidenced.

There is no mention of revenue, customers, or adoption beyond the hackathon submission. No evidence of user engagement, retention, or market traction.

Not evidenced.

The description does not reference competitors or market positioning in relation to existing tools for interview preparation or AI avatars.

• The product is described as a hackathon submission with MVP1/MVP2 boundaries — no evidence of commercial viability or user adoption.
• No pricing, monetization, or business model is stated.
• The author is listed as a single individual ("CyberLynx Filipovikj"), which raises questions about scalability and team capacity.
• The product is Windows-first and local-first, limiting its potential reach without broader platform support.
• The description includes challenges around disclosure, consent, and safety — suggesting that these are still evolving technical or design issues.

1. What is the intended business model for Presence?
2. Are there any users beyond the hackathon submission? If so, how many?
3. How does the team plan to scale beyond a single-person development effort?
4. What are the key technical challenges that remain unresolved before commercial release?
5. Is there any evidence of market demand or interest from potential users beyond the author’s own use case?