Replicate Automation Platform For Reuse
Budget: £10 – £15 GBP
I’m taking an in-house automation platform—built with GoHighLevel workflows, Python services, an OpenAI-powered ML layer, and a structured Postgres back end—and standing up an identical version for a partner company. You’ll receive full access to the running environment so you can study the data model, UI flows, and API hand-offs, then rebuild each piece in a fresh stack under the new organisation’s credentials.
What the platform already has:
• Database management: Postgres with custom schemas, seed data, and nightly jobs
• User interface: GoHighLevel pages, funnels, and dashboard widgets
• API integrations: several third-party services hit from Python micro-services
Deliverables
• A like-for-like replica deployed to a clean cloud environment
• Recreated GoHighLevel assets (funnels, triggers, automations) functioning exactly as in the source instance
• Backend codebase (Python) in a private Git repo, containerised for easy spin-up
• Verified ML endpoints calling the same OpenAI models with identical outputs
• Updated .env template plus concise deployment and hand-over documentation
• Smoke-test report showing UI → backend → ML → external API flow works without regressions
Success is measured by the new company logging in and operating the system with no perceivable difference from the original. An initial working copy inside two weeks would be ideal, followed by a short feedback cycle for polish. If you’ve migrated or white-labelled platforms before, let me know—your experience there will help us move even faster.
What the platform already has:
• Database management: Postgres with custom schemas, seed data, and nightly jobs
• User interface: GoHighLevel pages, funnels, and dashboard widgets
• API integrations: several third-party services hit from Python micro-services
Deliverables
• A like-for-like replica deployed to a clean cloud environment
• Recreated GoHighLevel assets (funnels, triggers, automations) functioning exactly as in the source instance
• Backend codebase (Python) in a private Git repo, containerised for easy spin-up
• Verified ML endpoints calling the same OpenAI models with identical outputs
• Updated .env template plus concise deployment and hand-over documentation
• Smoke-test report showing UI → backend → ML → external API flow works without regressions
Success is measured by the new company logging in and operating the system with no perceivable difference from the original. An initial working copy inside two weeks would be ideal, followed by a short feedback cycle for polish. If you’ve migrated or white-labelled platforms before, let me know—your experience there will help us move even faster.
Related categories:
Python
Ruby on Rails
Django
Software Architecture
PostgreSQL
API Development
OpenAI
GoHighLevel