AI Copilot for Modern Marketing Teams

Hacker News

Hey HN'ers! Hope you're doing well Today I'm launching this startup that I've been working on for some months now. It's an AI copilot for Modern Marketing Teams. Basically you describe your business to us. Be it by a simple text description, or something more complex like uploading images, powerpoint presentations, word docs, etc... Anything that you upload will be used by a LLM to then: 1. Brainstorm content ideas 2. Turn those content ideas either into visual social media posts (we do linkedin and instagram carousels for now) 3. Written content like blog posts, ad copy, cold emails etc... (where we do provide a real time collaboration feature thanks to liveblocks!) Besides those main features we also allow you to: - Create your own brand voice, so you don't sound robotic like all other ChatGPT generators. - Define Brand Safety Rules. These are strict rules that aren't based on AI so you are perfectly sure that your texts ALWAYS follow these rules. Thanks in advance, I hope you like the tool. I'm open for your feedback Mike PD: Obligatory Tech Stack: - Next.js - Prisma - PostgreSQL - tRPC - zod - TailwindCSS - Shadcn/ui - LiveBlocks - ChatGPT API - TipTap editor - Posthog

Visit product View on Hacker NewsApr 15, 2024

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2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: email, visual, chatgpt · Missing: mac, agents, macos

97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, way · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat, real time · Missing: web3, crypto, cryptocurrency

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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