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SaaS / Sales Tech
SaaS · Sales Tech · AI CRM

LinkedIn Outreach Platform

Case Study: AI-Powered LinkedIn Outreach Platform & CRM — campaign automation, multi-account control, and LLM + RAG messaging in one workspace.

Salesforce & AIFull-Stack EngineeringDevOps & Cloud Architecture
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5×

Volume

3.2×

Faster Replies

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SaaS · Sales Tech · AI CRM

LinkedIn Outreach Platform

Product Engineer · AI Integration

Case Study: AI-Powered LinkedIn Outreach Platform & CRM — campaign automation, multi-account control, and LLM + RAG messaging in one workspace.

SaaS / Sales TechReactTypeScriptNode.jsPostgreSQLRedisOpenAILLMRAG

5×

Volume

3.2×

Faster Replies

48%

Reply Quality

60%

Less Manual

LinkedIn Outreach Platform overview

Executive Summary

Outreach teams needed volume without generic-sounding automation.

We engineered a React and TypeScript CRM with Node.js APIs, PostgreSQL, Redis, and an OpenAI-powered LLM layer with RAG personalisation — so multi-account LinkedIn campaigns stay efficient, on-brand, and measurable.

Product UI

Project Screens

Salesforce Lightning Web Component screens from the loan origination platform — application intake, underwriting risk assessment, and pipeline Kanban — each built for financial services lending teams.

Multi-Device Outreach CRM Workspace — Salesforce loan origination platform UI
Screen 01

Multi-Device Outreach CRM Workspace

Campaign automation, multi-account control, and analytics in one clean workspace across laptop, tablet, and phone.

This AI-powered LinkedIn outreach CRM streamlines professional communication at scale. Teams run campaigns, manage contacts, and oversee multiple LinkedIn accounts from a single responsive workspace — volume without losing voice.

  • Responsive dashboard for desktop, tablet, and mobile
  • KPI cards for emails, campaigns, accounts, and credits
  • Activity charts and recent campaign status
  • Quick actions for campaign and contact workflows
ReactTypeScriptResponsive UXCRM
AI Messaging & Campaign Analytics — Salesforce loan origination platform UI
Screen 02

AI Messaging & Campaign Analytics

LLM-assisted message generation, RAG-grounded personalisation, and real-time performance dashboards.

An AI messaging layer uses LLMs with retrieval-augmented context so sequences stay on-brand across industries. Intent-based lead classification, reply suggestions, and Redis-backed real-time status keep multi-account outreach fast, secure, and measurable.

  • Campaign builder with sequenced follow-ups
  • LLM message generation and AI reply suggestions
  • RAG-grounded personalisation from lead and industry context
  • Real-time dashboards for engagement and continuity
OpenAILLMRAGNode.jsPostgreSQLRedis

The Challenge

Automating LinkedIn outreach risked generic messaging, account chaos, and cluttered analytics.

  • •Preventing messages from sounding generic despite automation.
  • •Maintaining tone consistency across industries and lead types.
  • •Managing multiple LinkedIn accounts without added complexity.
  • •Showing detailed analytics without cluttering the UI.
  • •Ensuring performance and security for connected accounts.

The Solution

We built a campaign engine, multi-account workspace, AI messaging layer, and analytics dashboards on a modern SaaS stack.

Key Features & Technical Implementation

01

Campaign & Sequence Engine

Structured sequences with flow control and per-stage personalisation.

Technical Detail: Node.js orchestration with PostgreSQL persistence for campaign state.

02

Multi-Account Workspace

Secure multi-LinkedIn-account management with real-time status.

Technical Detail: Redis-backed status and admin oversight for connected accounts.

03

LLM + RAG Messaging

Context-aware generation, reply suggestions, and intent classification.

Technical Detail: OpenAI LLMs with retrieval-augmented personalisation from lead context.

Technical Architecture

React/TypeScript clients talk to Node.js APIs; PostgreSQL stores CRM entities; Redis accelerates account status; OpenAI LLMs with RAG retrieve lead and industry context before generating outreach copy.

The Results

5×

Volume

Higher outreach volume per rep.

3.2×

Faster Replies

Quicker reply turnaround.

48%

Reply Quality

Improvement from AI-assisted messaging.

60%

Less Manual

Reduction in manual messaging effort.

  • 5× higher outreach volume per rep
  • 3.2× faster reply turnaround
  • 48% improvement in reply quality
  • 60% less manual messaging effort

Technology Stack

ReactTypeScriptNode.jsPostgreSQLRedisOpenAILLMRAG

Conclusion

LLM and RAG-powered outreach turned LinkedIn automation into a governed CRM workspace — scale with voice, not spam.

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