Ghost Pepper vs Mediator.ai

Ghost Pepper is a macOS menu bar app that runs Whisper-based speech recognition and meeting transcription entirely on-device via Apple Silicon — no internet connection required, no audio leaving your machine. Hold Control to dictate into any text field; it transcribes and pastes the result in seconds. For meetings, it records calls and generates full transcripts, notes, and AI summaries saved as local markdown files. The app supports multiple model sizes from a 75MB fast model to a 1.4GB multilingual option covering 25+ languages. A local LLM layer (Qwen 3.5 variants) strips filler words and self-corrections from transcripts. The developer published a privacy audit confirming zero cloud API calls, tracking SDKs, or telemetry in the core functionality — an unusual level of transparency in this space. Built on WhisperKit and LLM.swift, Ghost Pepper requires macOS 14.0+ and Apple Silicon. It launched on Product Hunt today reaching #4 daily. For anyone running sensitive client calls, legal conversations, or just unwilling to feed voice data to cloud services, this fills a genuine gap that ElevenLabs, Otter.ai, and Whisper API don't touch.

Mediator.ai applies LLMs and Nash bargaining theory to real-world disputes, generating agreements that both parties would accept — including solutions neither side had imagined independently. The process is private by design: each party separately describes their position, priorities, and constraints. The AI then generates multiple candidate agreements, scores each one against both parties' stated needs, and iteratively refines proposals until reaching an optimal solution. Use cases range from founder equity disputes and contractor payment conflicts to shared housing arrangements and inheritance disagreements. The system's key insight is that human negotiation is systematically bad at identifying the entire solution space — we anchor on positions, not interests. By modeling both parties' utility functions simultaneously, the AI can find Pareto-optimal outcomes that pure adversarial negotiation often misses entirely. With 159 Hacker News points, the response was genuinely enthusiastic — and the concept is hard to dismiss. Nash bargaining as a formalism has decades of academic credibility; what's new is making it accessible via natural language input. The pricing isn't published yet and the team is small, but the application domain (legal, HR, personal disputes) is enormous if they can nail trust and confidentiality.