s3-lambda
Viral Manager
Trendpop
Exolyt
Pentos.co
VidIQ
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HypeAuditor
Viral Manager is an AI-powered viral intelligence platform for content creators and social media agencies on Instagram and TikTok.
It replaces hours of manual scrolling with automated research: AI monitors public content in real time, your own accounts and your competitors, and surfaces the Reels and TikToks gaining momentum in your specific niche, refreshed every hour. Each post gets a relative virality score, a multiplier versus the account's own baseline (e.g. x3.43 =3.43x its usual reach), so you catch true breakout content instead of just big accounts.
Every viral post is then broken down by AI: hook, narrative structure, viral psychology and editing, with automatic transcript and caption extraction. You understand exactly why a piece of content works, then copy the script or generate a variant tailored to your niche.
For agencies, Viral Manager goes beyond analytics into production. Assign a viral reference directly to a creator with directives, a deadline and a reference asset. Role-based workspaces keep managers, VAs and creators aligned, managers oversee, VAs build briefs, creators receive their missions. Track every step, filmed, sent and approved, in one dashboard with no WhatsApp chains or scattered spreadsheets. A centralized asset library and multi-format adaptation keep the whole team producing from a single source of truth.
Viral Manager connects to Instagram Business/Creator and TikTok accounts for official analytics, and supports draft publishing straight to your TikTok inbox. It is built on a secure multi-tenant architecture with role-based access control, encrypted cloud storage and GDPR-compliant consent management.
Compatible with Instagram and TikTok, Viral Manager is made for creators and agencies who want to stop guessing what performs and start scaling with data, combining viral content intelligence with a real creator production workflow in one tool.
Viral ManagerViral Manager's answer:
Next.js 14 (App Router) and TypeScript, Supabase (Postgres, Auth, Storage with row-level security)
Viral Manager's answer:
Viral Manager combines two things most tools keep separate: real-time viral content intelligence and a full creator production workflow. AI monitors public Instagram and TikTok content, scores each post against the account's own baseline to reveal true breakout hits, and breaks down exactly why they work, hook, structure, psychology, editing. Then, in the same tool, you turn that insight into action: assign viral references to your creators, brief them, and track production from filmed to approved. It's the bridge between "what's going viral" and "get it made."
Viral Manager's answer:
Most tools stop at analytics, they show you numbers, then leave you to act elsewhere. Viral Manager goes further. Its relative virality score surfaces genuine outliers instead of just big accounts, its AI breakdown tells you why content works so you can replicate it, and its built-in assignment system turns insight into briefed, tracked production for your whole team. No juggling a analytics tool, a swipe file, WhatsApp and spreadsheets, it's viral research and creator workflow in one place, built specifically for Instagram and TikTok short-form.
Viral Manager's answer:
Content creators and social media agencies producing short-form video on Instagram and TikTok. This includes UGC creators, growth-focused solo creators, and agencies managing rosters of creators with managers and virtual assistants who need to detect trends, brief talent, and ship content fast.
Viral Manager's answer:
Viral Manager was born from a simple frustration: growing on Instagram and TikTok meant endless scrolling to guess what might perform, then chaotic production over WhatsApp and spreadsheets. Creators and agencies were burning hours on manual research and losing viral windows. We built Viral Manager to let AI do the research: monitoring public content, scoring virality, and explaining why content works, and to give teams one place to turn those insights into briefed, tracked creator assignments. The goal: stop guessing, start scaling with data.
