IBM_Hackathon_Report/ibm_ai_tools_usage.md

IBM watsonx Usage Report

Overview

ClaimCheck AI leverages IBM watsonx as the backbone for claim verification.
The system uses IBM watsonx.ai’s large language models and embedding capabilities to handle:

1. Text Retrieval (RAG)
2. Claim Verification
3. Evidence Reranking
4. (Optionally) IBM Speech-to-Text for transcription.

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Agents & IBM Integration

1. Transcriber Agent

• Goal: Convert audio from Zoom/phone calls to text.
• IBM Usage: Can integrate IBM Speech-to-Text (STT) to provide enterprise-grade transcription accuracy.
• Inputs: WAV/MP3/OGG audio file.
• Outputs: JSON array of { speaker, start, end, text }.

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2. Claim Extractor Agent

• Goal: Identify factual statements in the transcript.
• IBM Usage: Powered by IBM watsonx.ai LLM (Prompt Lab) to output JSON with { claim_text, speaker, start, end }.

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3. Retriever Agent

• Goal: Retrieve relevant knowledge base snippets to support or refute claims.
• IBM Usage:
  • IBM Text Embeddings: Generates semantic vector representations of KB snippets and claims.
  • FAISS Vector Search: Finds top-K relevant evidence from local index.
  • IBM Rerank API: Orders results by relevance.
• Benefit: Reduces false positives in evidence retrieval.

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4. Verifier Agent

• Goal: Cross-check each claim against retrieved evidence.
• IBM Usage: LLM prompt to classify as "Supported", "Contradicted", or "Unverifiable".
• Output: Verdicts with reasoning.

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5. Summarizer Agent

• Goal: Produce final human-readable report.
• IBM Usage: LLM summarization model to combine claims, evidence, and verdicts into structured output.

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Deployment & Scalability

While deployment is not in the scope of this hackathon, in a production setting:

• IBM watsonx.ai models can run in a secure IBM Cloud environment.
• IBM Orchestrate could be used to automate claim verification workflows (triggered after each meeting).
• IBM Code Assistant could accelerate code integration for enterprise clients.
• Scalable Vector Store: IBM Cloud Object Storage could hold large KB datasets for retrieval.

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Required Capabilities & Datasets

• KB Sources: SLA documents, compliance policies, contractual clauses, product documentation.
• Integrations: Zoom/Teams API for call recordings.
• Agents: 5 specialized agents as described.
• IBM Services:
  • Text Embeddings API
  • Text Rerank API
  • LLM Prompting via Prompt Lab
  • (Optional) Speech-to-Text

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Why IBM watsonx is Critical

• Enterprise readiness — Secure, compliant AI processing.
• High accuracy retrieval — Embeddings + Rerank reduce noise.
• Custom KB adaptability — Works across industries.
• Unified ecosystem — AI models, APIs, and orchestration tools in one platform.

By combining these capabilities, ClaimCheck AI transforms unstructured meeting dialogue into evidence-backed, compliance-ready reports in near real-time.