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Add BargAIner to showcase
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‎authors/anton-schedel.yml‎

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name: Anton Schedel
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avatar: "https://github.com/anton-schedel.png"
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bio: "Builder focused on AI apps and automation."
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location: "Munich, Germany"
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isElevenLabs: false
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socials:
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- label: GitHub
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url: "https://github.com/anton-schedel"
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- label: LinkedIn
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url: "https://www.linkedin.com/in/anton-schedel-763533221/"

‎authors/max-schallermayer.yml‎

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name: Max Schallermayer
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avatar: "https://github.com/MaxSchaTUM.png"
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bio: "Builder interested in AI systems and product engineering."
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location: "Munich, Germany"
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isElevenLabs: false
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socials:
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- label: GitHub
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url: "https://github.com/MaxSchaTUM"
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- label: LinkedIn
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url: "https://www.linkedin.com/in/max-schallermayer-51994816a/"

‎authors/nikolai-khalatiani.yml‎

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name: Nikolai Khalatiani
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avatar: "https://github.com/nikakhalatiani.png"
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bio: "Builder at TUM.ai; working on voice-first and agentic applications."
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location: "Munich, Germany"
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isElevenLabs: false
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socials:
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- label: GitHub
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url: "https://github.com/nikakhalatiani"
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- label: LinkedIn
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url: "https://www.linkedin.com/in/nikolai-khalatiani/"

‎authors/oskar-kraak.yml‎

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name: Oskar Kraak
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avatar: "https://github.com/oskarkraak.png"
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bio: "Builder focused on AI products and applied ML."
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location: "Munich, Germany"
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isElevenLabs: false
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socials:
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- label: GitHub
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url: "https://github.com/oskarkraak"
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- label: LinkedIn
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url: "https://www.linkedin.com/in/oskarkraak/"

‎projects/bargainer.mdx‎

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---
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title: BargAIner
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description: Real-time procurement negotiation assistant that listens to vendor calls, flags risky claims, and suggests data-backed counter-arguments.
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authorIds:
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- max-schallermayer
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- nikolai-khalatiani
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- anton-schedel
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- oskar-kraak
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categories:
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- speech-to-text
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- agents
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isFeatured: false
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date: "2025-01-20"
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image: /images/bargainer.png
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repoUrl: https://github.com/bargAInerTUMAI/bargAIner
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videoUrl: https://drive.google.com/file/d/1PBAoM1JAaKA4B0a8TtIj3PJG-ObuC9Sl/view?usp=sharing
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---
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# BargAIner
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## Overview
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BargAIner is a desktop application providing real-time AI assistance during procurement negotiations—built for Software Migration & Cloud Modernization deals. It listens to vendor conversations, detects claims that could negatively impact the buyer (pricing, timelines, scope), and generates instant counter-arguments backed by data.
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ElevenLabs is used for **real-time Speech-to-Text via Scribe**, streaming transcripts into the UI and agent pipeline.
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## Key Features
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- **Real-time Speech-to-Text (ElevenLabs Scribe):** Live transcription with VAD-based segmentation
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- **Mic + system audio capture:** Captures both sides of the conversation
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- **Claim detection:** Flags risky vendor claims (rates, scope exclusions, timeline pressure)
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- **Fact verification:** Checks an internal knowledge base + web search benchmarks
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- **Counter-argument generation:** Produces data-backed responses in real time
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- **Wrap-up + action items:** Detects summaries and extracts next steps; exports to PDF
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- **Post-negotiation feedback:** Scoring, tactics assessment, and improvement suggestions
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## How It Works
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1. **Electron frontend** captures microphone + system audio.
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2. Audio is streamed to **ElevenLabs Scribe via WebSocket** for live transcription.
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3. Transcripts are sent to a backend agent loop (Cerebras) which:
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- detects triggers (scope, pricing, staffing rates, timeline),
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- verifies claims against local documents (knowledge base),
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- pulls benchmarks via web search (Tavily),
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- generates counter-arguments and action items.
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4. The UI shows real-time transcripts, suggestions, and wrap-up/action items.
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## Technologies Used
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- **ElevenLabs Scribe (Speech-to-Text, WebSocket streaming)**
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- Electron, React, TypeScript, Node.js, Express
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- Cerebras (fast inference)
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- Tavily (web search)
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- Vercel AI SDK (agent framework)
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## Getting Started
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Full setup instructions are in the repository README:
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https://github.com/bargAInerTUMAI/bargAIner
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## Demo
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See the repository for instructions, or checkout our live demo at:
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https://drive.google.com/file/d/1PBAoM1JAaKA4B0a8TtIj3PJG-ObuC9Sl/view?usp=sharing
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## Future Plans
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- Add more negotiation “personas” and configurable playbooks
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- Improve benchmark sourcing and citations for claims
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- Ship a hosted demo / packaged releases for easier testing
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## Acknowledgments
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Built at the TUM.ai Hackathon by:
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- Max Schallermayer
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- Nikolai Khalatiani
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- Anton Schedel
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- Oskar Kraak

‎projects/images/bargainer.png‎

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