SEO Engine: Agentic Content Strategy
Case Study: LOOM Labs

SEO Engine: Agentic Content Strategy

High-Level Impact

Ongoing project. Revealed Summer 2026. Architecting a unified 'Brand Brain' for automated, brand-aware multi-channel campaign generation.

Project Metadata

  • CategoryAI / Cloud Automation / Marketing
  • ClientLOOM Labs

Core Components

Next.js 15 Management Dashboard
Genkit & Gemini 1.5 Pro Agentic Workflows
Knowledge Layer 'Brand Brain' (PDF/CSV Parsing)
Automated Visual Asset Creation (Imagen)
Multi-Agent Internet Research Tools
JSON-LD Technical Schema Engine

Business Objectives

Scale Organic Reach via automated Pillar and Cluster models
Reduce Operational Costs by replacing manual keyword research
Maintain 100% Brand Consistency through centralized Knowledge Layers
Automate technical JSON-LD schema and metadata generation
Produce tailored social assets for 5+ platforms in a single click
Enable real-world agentic internet research for factual accuracy

Solution Design

"Automate high-level content strategy and the production cycle by leveraging agentic AI to scale organic reach while ensuring factual brand consistency."

Confidential. System utilizes recursive multi-agent research loops and production pipelines. Strategic logic reveal scheduled for Summer 2026.

Project FAQs

    SEO Engine: Agentic Content Strategy | LOOM Labs Case Study | Pawan H Samarakoon