AI Sales Coach (Automation Engine)

Project Overview

This system analyzes sales conversations using LLMs enriched with historical customer context. By synthesizing the current call with prior interactions, it delivers continuity-aware coaching that reflects long-term relationship dynamics rather than isolated calls. The result is consistent, scalable sales coaching grounded in real commercial situations.

NoteRole

End-to-end owner: system design, LLM orchestration, backend implementation, and analytics logic.

NoteTools

FastAPI • Python • LLM APIs • Retrieval-Augmented Generation (RAG) • Async Event Processing

NoteDomain

B2B Sales Analytics • Revenue Enablement • Conversational Intelligence

Key Features & Components

Contextual Performance Coaching

Generates targeted observations and concrete next-step recommendations for sales reps, grounded in B2B sales methodology and sales psychology.

Historical Conversation Synthesis

Automatically retrieves and integrates the latest customer interactions to ensure coaching reflects relationship history and momentum.

Intelligent Lead Tiering

Classifies interactions to focus analysis on revenue-critical conversations and filter operational noise.

Robust Speaker Mapping

Heuristic diarization logic reliably distinguishes Operator vs. Client across heterogeneous transcription formats and call directions.

System architecture diagram

System architecture diagram

Implementation

Asynchronous Event Processing

FastAPI background tasks enable high-throughput webhook ingestion without blocking upstream transcription services.

Context-Enriched RAG

Caller ID–based retrieval injects historical summaries into the LLM pipeline for longitudinal analysis.

Bimodal LLM Orchestration

Lightweight models handle classification and routing, while higher-reasoning models generate nuanced coaching insights.

Automated Insights Delivery

Markdown-based analyses are rendered into HTML and delivered directly via email for immediate sales team consumption.

Outcomes & Impact

TipNear-Real-Time Feedback Loops

Coaching latency reduced from days to minutes, enabling faster behavioral adjustment.

TipChurn Risk Detection

Early identification of sentiment shifts, objections, and signals tied to retention risk.

TipScalable Sales Expertise

Encodes senior-level B2B sales knowledge into a consistent, automated coaching framework.

Skills Demonstrated

LLM Orchestration • Retrieval-Augmented Generation (RAG) • Context-Aware LLM Synthesis • Conversational Data Modeling • Sales & Revenue Analytics • B2B Sales Methodology • Asynchronous API Design • Event-Driven Processing • Prompt Engineering • Speaker Diarization Logic • Automated Insight Generation • End-to-End System Design

Apply This to Your Business

Want to scale sales coaching without it becoming generic? Let’s talk about how I help turn real sales conversations into actionable, context-aware insights.

See Also