Case Study — SaaS · AI Campaigns · USA

HiveGPT
AI Campaign Platform

Enterprise AI platform for automated marketing campaign generation, performance prediction, and creative optimisation — built at HiveGPT Inc., Seattle USA.

Architecture visualization
SYSTEM_ARCHITECTURE_V2.4
NODE_SECURE
Enterprise
Scale
Multi-Tenant
Architecture
USA
HiveGPT Inc.
OpenAI
AI Engine
Platform

HiveGPT is an enterprise SaaS platform that uses AI to automate marketing campaign creation, predict performance across channels, and optimise creative assets at scale. Vijay led senior AI product engineering at HiveGPT Inc. (USA), building core platform infrastructure.

Role

Senior AI Product Engineering — responsible for multi-tenant SaaS architecture, OpenAI API integration, campaign generation pipelines, performance prediction models, and production deployment on Azure. Deep collaboration with US product and design teams.

  CASE STUDY 02 · ENTERPRISE AI PLATFORM
🧬
HiveGPT
Private Enterprise AI · RAG · LLM Orchestration

Your Company's Knowledge,
Finally Queryable.

HiveGPT is a private, enterprise-grade AI knowledge platform we built to give organisations a secure ChatGPT-style interface trained exclusively on their own documents, SOPs, and institutional knowledge — with zero data leaving their infrastructure.

92%
Reduction in time spent searching internal docs and SharePoint folders
< 2s
Average query response time across 500K+ document corpus
100%
Private deployment — all data stays on client's own cloud or on-premise
40+
Departments using HiveGPT daily within 60 days of launch
$2M/year lost in
knowledge silos

The client — a 2,000-person professional services firm — had 14 years of project reports, SOPs, legal documents, HR policies, and client deliverables spread across SharePoint, Google Drive, email, and local servers. New employees took 6 months to become productive. Senior staff spent 3+ hours daily re-answering questions that had been answered before.

Worse — they couldn't use ChatGPT or any public AI because of strict data governance and client confidentiality requirements. They needed the power of GPT without the privacy risk.

  • Document Intelligence: Ingests PDFs, Word docs, spreadsheets, emails, and web pages into a semantic vector database
  • Conversational Query: Employees ask natural-language questions and get sourced, cited answers from internal docs
  • Role-Based Access: Finance team sees finance docs; HR sees HR docs — zero cross-contamination
  • Hybrid LLM: Uses private Azure OpenAI for sensitive queries; falls back to lighter local models for routine tasks
  • Audit Trail: Every query logged for compliance — who asked what, when, and what answer was given
🔒
Zero Data Egress
Deployed entirely within the client's Azure or AWS tenant. No data is ever sent to third-party AI providers. SOC2 and HIPAA compliant by design.
🔗
Connects Everything
SharePoint, Confluence, Google Drive, Jira, Salesforce, SAP, email archives — HiveGPT ingests from 20+ enterprise data sources via pre-built connectors.
📈
Gets Smarter Daily
Continuous ingestion pipeline — new documents are indexed within minutes of upload. The knowledge base never goes stale.
STACK
Next.js · .NET Core · Azure OpenAI · Pinecone Vector DB · LangChain · Azure AD SSO · Docker · Kubernetes
Implementation in 8 Weeks
WEEK 01–02
Discovery & Data Audit
Mapped all data sources, defined access policies, established compliance framework
WEEK 03–04
Ingestion Pipeline
Built connectors, vectorised 400K+ documents, tuned embedding models
WEEK 05–06
RAG Engine & UI
Query orchestration, citation engine, conversational interface with SSO
WEEK 07–08
Rollout & Training
Phased department rollout, staff onboarding, feedback loops integrated
Showcase

Campaign Intelligence

Visualizing the AI-powered campaign generation and predictive performance dashboards.

Campaign Generation Flow
Dashboard
Hive3
Hive4
Hive5
Hive6
Logo White
Personalised Landing Page
Responsible AI
🎥 Video Demo

Campaign Generation Flow

1 / 9

Key Contributions
🤖
AI Campaign Engine

LLM-powered campaign brief → ad copy → creative variants pipeline. Multi-variant generation with brand voice consistency.

🏢
Multi-Tenant Architecture

Secure tenant isolation, per-tenant LLM configuration, usage metering, and billing integration.

📊
Performance Prediction

ML models predicting CTR, conversion rate, and ROAS before campaign launch based on historical data.

☁️
Azure Infrastructure

Production deployment on Azure — containerised microservices, autoscaling, monitoring, and zero-downtime deployments.

Tech Stack
.NET CoreReactOpenAI APIAzureDockerPostgreSQLRedisMulti-tenant SaaSTypeScriptSignalR