8 text documents in .md format with technical documentation and application architecture

LandingForge — AI landing page builder and hosting for micro-agencies

Name: LandingForge — AI landing page builder and hosting for micro-agencies
Brand: Fizoni
Price: 29 USD
Availability: InStock

Version 1.0.0 Updated: 2026-09-13 Quality: 82/100

A Next.js web app that turns client data into a ready-to-publish landing page: text generation, HTML/CSS assembly, deployment to a subdomain with SSL, and built-in lead analytics.

📁 What is inside (ZIP, 9 files)

01_architecture.md
02_template_engine.md
03_ai_content_generator.md
04_image_pipeline.md
05_landing_builder_ui.md
06_publishing_hosting.md
07_analytics_leads.md
08_deployment_guide.md
README.md

Problem

Micro-agencies spend hours manually assembling landing pages for clients: copying texts from ChatGPT, hand-coding HTML/CSS, and separately handling hosting, SSL, and analytics. ChatGPT doesn't produce a ready-to-publish website — it only generates text. As a result, creating a single page stretches over a day or more, and margins drop.

Solution

LandingForge automates the entire process: you enter the client's data, choose a template, a module powered by the OpenAI API generates the copy and SEO meta, an image pipeline prepares the logo and backgrounds, and server-side rendering assembles the HTML/CSS. The system then publishes a static site on a subdomain or custom domain with SSL and CDN, while built-in analytics and lead capture with Telegram/Email notifications close the feedback loop. All in a single app built on Next.js + Prisma + PostgreSQL.

More details

LandingForge is a ready-made web application for micro-agencies that covers the entire landing page creation cycle: from the client brief to a published website with analytics. You enter the company name, services, benefits, and contacts, choose one of the preset templates (hero, features, pricing, form) — and the system uses server-side rendering to assemble a fully functional HTML/CSS website. No copying from ChatGPT and no manual coding: the texts are generated by a module based on the OpenAI API, images undergo automatic optimization, and publishing happens in one click. The architecture is built on Next.js + Tailwind CSS + Prisma + PostgreSQL. It is a monolithic application that is easy to deploy in Docker and does not require a separate frontend. The DB schema (User, Client, Landing, Template, Lead) is described in the documentation, including migrations and relationships between entities. Templates are stored as JSON schemas, which makes it possible to add new blocks without rewriting code. The AI generation module works with the OpenAI API: separate prompts for headlines, service descriptions, CTAs, and SEO meta. It includes validation and post-processing of responses, caching of repeated requests, and error handling with limits. This removes the risk of "raw" text and unnecessary API costs. The image pipeline accepts the client's logo and photos, automatically converts them to WebP, resizes them to the required dimensions, and, if necessary, generates background images via DALL-E or selects them via the Unsplash API. All files are stored in S3-compatible storage, which simplifies scaling and reduces server load. Publishing works like this: the system generates a static website, deploys it to a subdomain such as client.agency.com or to a custom domain, configures SSL and CDN, and maintains versioning of landing pages. The built-in tracker collects views and conversions, the request form sends leads to Telegram/Email, and the dashboard shows metrics (views, CTR, leads) with export capability. All documentation on deployment, environment variables, and connecting external services is included. The product is delivered as a set of markdown files with complete technical documentation and architecture, from which the application can be built. This is not a prompt pack or a "how to do it" guide — it is a detailed system project, ready for implementation and launch.

Features

Step-by-step builder wizard: template selection → client data entry → preview → publishing
JSON schema of templates with hero, features, pricing, form blocks and support for custom colors and fonts
AI text generation via OpenAI API: headlines, service descriptions, CTAs, SEO meta with validation, caching and limits
Image pipeline: logo and photo upload, conversion to WebP, resizing, background generation via DALL-E or Unsplash, storage in S3
Publishing a static site to the client.agency.com subdomain or a custom domain with SSL, CDN and versioning
Built-in analytics: visit and conversion tracker, form lead capture, Telegram/Email notifications, dashboard with metrics and export
Prisma DB schema: User, Client, Landing, Template, Lead with migrations and relations
Docker deployment with environment variable configuration and OpenAI, S3, Telegram integration

What you get

01_architecture.md — application architecture, stack (Next.js + Tailwind + Prisma + PostgreSQL), DB schema and data flows
02_template_engine.md — template engine: JSON schema of blocks, substitution rules, server-side HTML/CSS rendering
03_ai_content_generator.md — text generation module via OpenAI API: prompts, validation, caching, limits
04_image_pipeline.md — image pipeline: upload, WebP, resize, DALL-E/Unsplash, storage in S3
05_landing_builder_ui.md — builder interface: wizard, live block editor, validation, responsiveness
06_publishing_hosting.md — publishing mechanism: static build, deployment to subdomain/domain, SSL, CDN, versioning
07_analytics_leads.md — analytics and leads: tracker, lead capture, Telegram/Email notifications, dashboard, export
08_deployment_guide.md — deployment guide: environment, variables, migrations, Docker, monitoring

Installation guide

1. Study 01_architecture.md — determine the stack and DB schema. 2. Deploy PostgreSQL and configure Prisma according to the migrations from the documentation. 3. Follow 08_deployment_guide.md: configure the environment variables (OpenAI API key, S3 credentials, Telegram bot token). 4. Implement the template engine according to 02_template_engine.md and the AI generation module according to 03_ai_content_generator.md. 5. Connect the image pipeline according to 04_image_pipeline.md. 6. Build the builder interface according to 05_landing_builder_ui.md. 7. Set up publishing and hosting according to 06_publishing_hosting.md. 8. Implement analytics and lead capture according to 07_analytics_leads.md. 9. Run the application in Docker and verify the full cycle: data input → generation → publishing → lead.

Requirements

Node.js 18+, PostgreSQL 14+, Docker (optional), OpenAI API account, S3-compatible storage (AWS S3, MinIO, etc.), Telegram Bot Token (for notifications), a domain for publishing landing pages, basic skills in working with Next.js and Prisma

Options and pricing

Choose the level that suits you:

Basic — $17 · The main set of product files.
Standard — $29 · Full set + implementation guide.
Extended — $46 · Everything from Standard + extended materials and updates.

Frequently asked questions

What is included?

A Next.js web app that turns client data into a ready-to-publish landing page: text generation, HTML/CSS assembly, deployment to a subdomain with SSL, and built-in lead analytics.

In what format will I receive the files?

After payment you get a secure link and a ZIP archive with all materials. The link is shown on the order page and available via the Telegram bot.

How long is the download link valid?

The link is active for 24 hours, up to 5 downloads.

Do I need special skills?

The product is designed for entrepreneurs and specialists. A step-by-step guide is included; no programming skills required.

Can I get a refund?

For refunds, contact support: [email protected].