Promere.ai

AI image creators waste hours on prompt trial-and-error. You see a generated image you love, but you don't know what produced it — and even if you find a prompt that works in Midjourney, it doesn't translate to Flux or Seedream.

There's no shared intelligence layer for prompts: no way to search by what you want to see, no way to extract a recipe from an image, no way to organize what's working across models. Every D2C marketer, content creator, and AI artist rebuilds the same wheel with every project.

Promere is a prompt intelligence platform built on three core capabilities: semantic search across 6,800+ classified images, reverse-engineering any image into its 8-element prompt recipe, and model-specific formatting that translates the same recipe across 10 different AI models.

Where existing tools are either prompt galleries or generation engines, Promere is the layer underneath — the structured intelligence that makes prompts portable, searchable, and reusable across models. Built with semantic vector search on top of a classified visual taxonomy, it treats every prompt as data, not text.

Key decisions: chose pgvector over a dedicated vector database for cost simplicity, used Claude Sonnet for reverse-engineering because prompt extraction quality is non-negotiable, and built the entire platform single-handed in Cursor with Claude as the architecture partner.

01

Search by what you want to see

Type a description in plain English — "dramatic golden hour portrait with film grain" — and pgvector finds prompts that produced visually similar images.

02

Reverse-engineer any image

Upload a reference image and Promere breaks it into 8 elements: subject, lighting, style, composition, mood, technical settings, color palette, and negative prompt.

03

Format for any model

Same recipe, different syntax. Switch between Flux, Midjourney, Stable Diffusion, DALL-E, Nano Banana Pro, Seedream, Grok, and three more — each formatted to that model's prompting conventions.

04

Build your library

Save prompts, organize by collection, search your saved arsenal, and access from anywhere.

05

Learn the vocabulary

A visual glossary teaches what "anamorphic," "subsurface scattering," and "golden hour" actually look like — with real examples.

Supabase + pgvector eliminated the cost and complexity of a dedicated vector database. Cloudflare R2 made image storage essentially free at scale. Claude Sonnet was non-negotiable for reverse-engineering quality — the prompt extraction has to be accurate or the entire feature collapses.

Launching publicly across r/StableDiffusion, r/PPC, and Product Hunt to validate which audience converts first: AI artists looking for prompts, or D2C marketers scaling ad creative.

Building user submission for community-contributed prompts, model comparison views (same prompt across 10 models, side by side), and an API layer for ComfyUI and n8n integration.

Long-term, Promere becomes the connective layer between prompt creation, model execution, and workflow automation — the intelligence platform underneath every AI image workflow.