Real-Time AI Sales Coaching Assistant — Architecture, Stack & Cost Breakdown

Codersarts AI
4 days ago
3 min read

Overview

A growing category of "live conversation intelligence" tools listens to a sales call in real time, transcribes it instantly, and feeds the transcript to an LLM agent that returns objection-handling scripts and talking points — displayed on a dashboard the rep sees while still on the call. This is a productizable build pattern Codersarts AI delivers end-to-end for sales teams, call centers, recruiters, and support orgs, in any language.

The Pipeline


Audio (mic + system) → Streaming STT → Context/RAG Layer → LLM Agent → Live Dashboard

Browser captures rep audio + prospect audio via WebRTC
Audio streamed over WebSocket to a real-time STT engine
Live transcript chunks are matched against the client's sales playbook / objection library (RAG)
An LLM agent generates a short, actionable suggestion
Suggestion is pushed to a dashboard/overlay over WebSocket

Recommended Stack

Layer	Recommendation	Why
Audio capture	WebRTC (getUserMedia + getDisplayMedia)	Browser-native, no install required
STT	Deepgram Nova-3 (streaming)	5.26% WER, sub-300ms latency, $0.0077/min
Context / RAG	pgvector or Qdrant + chunked playbook	Keeps prompts small, current, and cheap
LLM agent	GPT-4.1-mini (escalate to GPT-4.1 for post-call summaries)	~150ms time-to-first-token, $0.40 / $1.60 per 1M tokens
Backend	Node.js (Fastify) + WebSocket server	Handles concurrent streaming sessions
Frontend	React overlay using CSS logical properties	RTL-ready out of the box (Hebrew, Arabic, English, etc.)
Hosting	Single-region deployment near the client (AWS / Fly.io)	Minimizes network round-trip

Latency Budget (Target: Under 1 Second)

Stage	Target
Audio chunking	50–100ms
STT interim result	150–300ms
RAG retrieval	50–100ms
LLM first token	150–250ms
UI push	<50ms
End-to-end	~500–800ms

Development Plan — 3–4 Week MVP

Milestone	Scope	Duration	Cost (USD)
M1	Audio capture + Deepgram streaming integration	Week 1	$1,500
M2	Playbook RAG ingestion + LLM agent integration	Week 2	$2,000
M3	Real-time dashboard/overlay (RTL-ready)	Week 3	$1,500
M4	Latency tuning, QA, deployment	Week 4	$1,500
MVP Total		3–4 weeks	$6,500

Phase 2 (quoted separately): multi-tenant architecture, CRM integrations (HubSpot/Salesforce), post-call analytics dashboard, multi-language support — typically $5,000–$10,000.

Monthly Running Cost — Worked Example

Assumptions: 10 sales reps × 4 active call-hours/day × 22 days = 880 call-hours/month, with one AI suggestion generated every 30 seconds during active speech (~800 input / 100 output tokens per call).

Component	Rate	Monthly Cost
Deepgram Nova-3 (streaming)	$0.0077/min	~$407
GPT-4.1-mini	$0.40 / $1.60 per 1M tokens	~$51
Hosting (WebSocket backend + dashboard)	Small VPS / Fly.io	~$75
Total		~$530/month

Swapping to GPT-4.1 ($5 / $15 per 1M tokens) for higher-quality suggestions raises the LLM line to ~$635/month, bringing the total to ~$1,115/month. Cost scales roughly linearly with active call volume — a 5-rep team runs at roughly half these figures.

Use Cases: Same Pipeline, Different Industries

The streaming STT + RAG-grounded LLM + live UI pattern is a horizontal capability — only the playbook/knowledge base and prompt logic change per client.

Use Case	Target Client	Real-Time AI Output
Sales call coaching	SaaS, real estate, insurance sales teams	Objection-handling scripts, next-best talking points
Customer support QA	Call centers, telecom, BPOs	Script/compliance adherence prompts, escalation flags
Recruiting interviews	Staffing agencies, HR teams	Competency-based follow-up questions, scoring cues
Debt collection compliance	Collections agencies, fintech	Real-time regulatory phrase flags (FDCPA/TCPA)
Insurance claims intake	Insurance carriers	Guided questioning, fraud-risk flags
Telehealth intake	Clinics, telemedicine platforms	Real-time documentation prompts, symptom checklists
Legal client intake	Law firms, legal tech	Case qualification prompts, conflict-check flags
Sales training simulators	Sales enablement teams	Live feedback during practice pitches
Multilingual support desks	Global support teams	Live translation + coaching overlay (RTL/LTR)

Why Codersarts AI

Codersarts AI builds and ships real-time conversational AI pipelines end-to-end — streaming STT integration, RAG-grounded prompting, latency-optimized backends, and live dashboards — for sales, support, and recruiting teams worldwide.