RRRavish Rana
All work
Multi-AgentLive demo

AI Marketing OS

A multi-agent marketing command center with 11 specialized AI tabs, a self-learning brain that extracts insights from approved outputs, real-time cost tracking, and brand context injected into every generation.

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Agent tabs
11
LLMs orchestrated
3
Extraction saving
3x

The problem

Marketing teams juggle a dozen tools and re-explain their brand to every AI prompt, with no memory and no visibility into what content costs.

How it works

A tabbed workspace routes each request through brand-context injection, brain retrieval, Claude generation and cost logging. Approved outputs feed a Haiku extraction pass that grows the brain for future generations.

Architecture

Browser (Next.js App Router)
   -> API routes /api/generate/[tab]
      - Brand context injection
      - Brain retrieval (top-k entries)
      - Claude Sonnet 4.6 generation
      - Cost logging to PostgreSQL
   -> Post-approval: Claude Haiku extracts insights -> brain

Highlights

  • 11 specialized agent tabs across the full funnel: strategy, copy, email sequences, social content, ad creatives, SEO, launch plans and more.
  • Self-learning brain: every approved output is analysed by Claude Haiku, which extracts reusable insights stored for future context.
  • Real-time cost tracking per generation, per tab and system-wide.
  • Brand context injection: voice, tone and positioning are prepended to every prompt automatically.
  • Dual-LLM architecture: Sonnet generates, Haiku extracts and classifies for a 3x saving on extraction.