AI/AIZENME
📞 RESEARCH · Deep Research Level: Beginner ⏱ 10 MIN Free & Open Source

Audit B2B Sales Calls with MEDDIC & Fabric analyze_sales_call

Great chat, then ghosted? Feed your sales call transcript into Fabric's `analyze_sales_call` pattern with MEDDIC scoring to spot missing Economic Buyers, weak pain quantification and next-step gaps.

CORE TOOLS Fabric (Open Source), Lark Minutes / Whisper, DeepSeek
BEST FOR B2B Account Executives, SaaS founders, sales managers, consultants
REQUIREMENTS Sales call transcript; any LLM
✦ WHY THIS WORKFLOW

Happy ears kill deals. Auditing every transcript against MEDDIC turns every discovery call into a structured coaching session.

✦ Interactive Workflow Animation Preview

Step-by-Step Action Checklist

0 / 4 Completed
READY-TO-USE PROMPT TEMPLATE
Open Official Tool / Repo ↗ 
Using the `danielmiessler/fabric` **analyze_sales_call** pattern and the **MEDDIC** framework, audit this B2B sales call transcript:
[Paste call transcript]
Output:
1) **Talk-to-Listen Ratio & Discovery Mistakes** (where the rep pitched prematurely);
2) **MEDDIC Scorecard (0-10 per pillar)** highlighting exact blind spots (especially Economic Buyer and Decision Process);
3) **Unspoken Objections & Competitor Signals**;
4) **Ready-to-Send Follow-Up Email** that locks in next steps and uncovers the missing MEDDIC pieces.
Use Cases & Tags:
B2B discovery call auditingSales manager coaching reviewsFounder-led sales qualificationObjection handling playbook extraction#fabric
MORE

Related AI Workflows

← Describe your idea on Home
RESEARCH · Deep Research
20 MIN

Deploy WorldMonitor Open-Source Real-Time Global OSINT & Geopolitical AI Dashboard

An open-source global intelligence command center with nearly 90k stars on GitHub! WorldMonitor brings military-grade situational awareness to your desktop. It fuses satellite feeds, maritime tracking, commodity supply chain alerts, geopolitical breaking news, and global infrastructure monitors into a unified interface—powered by local LLMs and MCP for autonomous debriefing and anomaly alerts.

WorldMonitor (Open Source)Python / DockerOpen-Source OSINT FeedsDeepSeek / Claude
Best for: Macro hedge fund analysts, cross-border trade executives, international relations researchers, journalists, geopolitical risk directors
Full guide ↗
RESEARCH · Deep Research
20 MIN

Deploy TradingAgents Multi-Agent LLM Framework for Collaborative Financial Quant Research & Risk Hedging

A viral financial multi-agent framework with 110k+ stars on GitHub! TradingAgents simulates an elite Wall Street quantitative hedge fund desk. It orchestrates Fundamental, Sentiment/News, Technical, and Risk Management Agents in structured debates and adversarial cross-examination—delivering institutional-grade research, DCF valuations, and VaR stress tests without emotional bias.

TradingAgents (Open Source)Python 3.10+DeepSeek-R1 / Claude 3.5 Sonnetyfinance
Best for: Quantitative traders, equity research analysts, portfolio managers, family office analysts, FinTech developers
Full guide ↗
RESEARCH · Deep Research
15 MIN

Extract Complex Dual-Column Papers, Tables & LaTeX Math into Clean Markdown with MinerU

The ultimate antidote to messy PDF extraction! MinerU (Magic-PDF) by Shanghai AI Lab is an open-source powerhouse with 23k+ stars. Engineered for complex dual-column academic layouts, merged tables, and intricate LaTeX mathematical formulas where standard OCR engines fail, it reconstructs natural reading flows and exports pristine Markdown ready for RAG pipelines.

MinerU / Magic-PDF (Open Source)PythonPyTorchCUDA
Best for: Academic researchers, patent attorneys, biotech analysts, enterprise knowledge architects, digital archivists
Full guide ↗
RESEARCH · Deep Research
15 MIN

Dual-Level Knowledge Graph RAG with HKU Open-Source LightRAG at 1% Cost of GraphRAG

Break free from shallow vector RAG and the crushing expense of Microsoft GraphRAG! Developed by HKU, LightRAG introduces dual-level graph retrieval (low-level specific entities + high-level thematic relationships). It speeds up indexing by 10x, slashes API token costs to 1%, and supports incremental document updates for nuanced multi-hop Q&A over complex domains.

LightRAG (Open Source)PythonOllama / DeepSeek APINetworkX
Best for: Financial analysts, legal compliance teams, enterprise knowledge managers, RAG developers, academic researchers
Full guide ↗
RESEARCH · Deep Research
15 MIN

Deploy Local DeepSeek-R1 for Autonomous `<think>` Chain-of-Thought Reasoning & Self-Reflection

DeepSeek-R1 is a global milestone in open-source AI, unlocking autonomous deep reasoning via pure reinforcement learning. Free from rigid prompt engineering, the model reflects, hypothesizes, and self-corrects inside `<think>` tags before answering. Deploy distilled models locally via Ollama or vLLM to solve complex code algorithms, legal loophole cross-auditing, and deep logic problems at zero cost.

DeepSeek-R1 (Open Source)Ollama / vLLMPythonOpen WebUI
Best for: System architects, algorithm engineers, corporate attorneys, academic researchers, strategy analysts, open-source AI geeks
Full guide ↗
RESEARCH · Deep Research
15 MIN

Long-Audio Meeting Transcription with Overlapped Speech Diarization via Open-Source MOSS-TD

MOSS-TD by Fudan University is an open-source long-form speech transcription and diarization system engineered for messy multi-speaker scenarios. Even during intense debates where people interrupt and talk over each other, MOSS-TD cleanly isolates overlapping audio tracks and assigns timestamps to every unique speaker.

MOSS-TD (Open Source)PyTorchONNX RuntimePython
Best for: Executive assistants, legal paralegals, investigative journalists, investment analysts, consultants, conference scribes
Full guide ↗