Executive Summary (TL;DR)
A full-stack, AI-driven content automation platform designed to generate personalized, brand-consistent press release (PR) content grounded in company documents — delivered in under 48 hours.
Problem / Opportunity
The global press release (PR) services market exceeds $3 billion in annual spend, yet remains largely untransformed by automation. Agency-based delivery timelines — often 5–7 days — do not align with the pace of product launches, fundraising, or media cycles. Evertise identified this as a high-margin, underserved market for scalable innovation.
Solution
Evertise built a document-grounded content generation platform using LLAMA 3.1, Vertex AI infrastructure, and LangChain orchestration. It allowed teams to upload brand materials, generate draft PRs with citations, and iterate in real time — all without human copywriters or agency delays.
Impact
- Replaced agency cycles with <2-day content generation
- Delivered scalable editorial quality across 100+ client accounts
- Enabled self-service workflows with compliance-ready outputs
- Directly linked to a recurring revenue model that drove a $10M valuation lift
Business Outcome & Strategic Leverage
- Introduced an AI-native PR automation product in a legacy-dominated $3B market
- Created switching friction through embedding lock-in and brand customization logic
- Used internally at Evertise and externally by 100+ clients
- Became a proof-point asset for fundraising and client acquisition
1. Strategic Context & Market Friction
The press release (PR) market is massive, but technologically stagnant. Most providers rely on manual writers, creating long delays and inconsistent tone. For startups, this undermines campaign timing, thought leadership, and funding momentum.
Evertise aimed to solve this by introducing intelligence and velocity into a space where copy quality and speed are paramount — and where no major players had built document-grounded workflows.
2. Objectives & Delivery Constraints
- Collapse PR turnaround time from 5–7 business days to under 48 hours
- Deliver brand-safe, verifiable copy grounded in client-uploaded content
- Support >95% editorial accuracy with minimal human revision
- Ensure model transparency and maintain sub-7s latency under load
3. Technical Architecture & Infrastructure Decisions
System Overview
- Model: LLAMA 3.1 — fine-tuned on 4M+ press releases to preserve structure and tone
- Retrieval Layer: LangChain pipelines using Vertex AI Feature Store embeddings for RAG retrieval
- Pipeline Automation: Vertex AI Pipelines coordinated data ingestion, tuning, and deployment
- Inference Layer: Vertex AI Prediction endpoints returned results in sub-7s
- Modularity: All services were microservice-based and callable via internal API
Design Rationale
- LangChain enabled prompt composition, re-ranking, and fallback handling
- Embedding structure supported document prioritization via tagging logic
- Stack enabled high reuse across verticals (e.g., SaaS, fintech, healthcare) with minimal adjustment
4. Implementation & System Workflows
- Clients uploaded brand content via secure intake
- Content was embedded, indexed, and scored for contextual proximity
- Query scaffolding handled prompt construction and inference orchestration
- Returned drafts included inline citations for traceability
- Clients could approve, request edits, or flag issues — all tracked in system logs
5. User Experience & Product Storytelling
- Editorless, no-code UI enabled non-technical teams to deploy professional PRs
- Outputs included hover-over citations, edit suggestions, and revision histories
- Admin dashboard tracked generation stats, source document coverage, and user sentiment
- Configurable tone levels allowed startup vs enterprise style tuning
6. Performance Outcomes & Measurable Impact
- Turnaround: Reduced to ~2 days from 5–7 business days
- Latency: Average generation time ~6.3s
- Editing: 35% reduction in manual revision effort
- Adoption: >100 clients onboarded; >10,000 PRs served
- Reliability: >99.9% uptime across inference services
7. Adoption & Market Strategy
- Warm-started via internal clients and B2B PR agencies
- Positioned as “developer-grade PR for marketing teams”
- Thought leadership content drove awareness, credibility, and trial
- Product-led growth model with optional onboarding concierge
8. Feedback-Driven Evolution
- Clients wanted finer tone control → added tone-tiered prompt weights
- Introduced multi-brand support for agencies
- Added token visualization to clarify which sources influenced generation
- Upcoming: long-form support, PDF ingestion, sentiment-aware rewrites
