See how I've helped businesses eliminate manual work and get back their hours every week.

Before automation: Team members spent hours every day manually searching news sites and research feeds, filtering for relevant stories, reading articles, summarizing updates for the team, and drafting LinkedIn posts.
After automation: Built a two-Zap system in Zapier that handles the full cycle — from raw news to a reviewed, publish-ready LinkedIn post.
Zap 1 — Draft Generator: Monitors multiple RSS feeds every 2 minutes for new articles. Each article is passed to AI, which assesses relevance against the company's defined focus areas and flags it as relevant or irrelevant. Irrelevant articles are filtered out. For relevant ones, AI generates a draft LinkedIn post and sends it directly to Slack for review.
Zap 2 — AI Editor: Once the team drops comments on the draft in Slack, a second Zap is triggered. It retrieves the comments, passes both the original draft and the feedback to AI, and sends a revised version of the post back to Slack — ready to review and publish.
Tools/Systems:

Before automation: Every time an email was sent to a new contact, someone had to manually add them to Monday CRM for tracking and Mailchimp for email campaigns, leading to missed contacts and inconsistent data.
After automation: Built a system that automatically captures every new email contact and syncs them to both Monday CRM and Mailchimp in real-time. No manual entry, no missed contacts, no data gaps.
Tools/Systems:

Before automation: Every Zoom cloud recording had to be downloaded manually, then uploaded to Dropbox one by one. From there, someone still had to open each file, read through the transcript, identify the client or prospect, locate the right folder, and move the file across four entity categories and multiple folder structures. Slow, repetitive, and easy to miss.
After automation: Connected Zoom directly to Dropbox so recordings land automatically no manual downloading or uploading. Then built a Claude skill that reads each new recording, pulls the transcript, matches it to the correct client or prospect using fuzzy entity recognition, determines the call type and division, and posts a structured set of sorting suggestions to Slack, including exact destination paths and any folders that need to be created. Nothing moves until approved. What used to be a multi-step manual process now takes a single confirmation.
Tools/Systems:

Before automation: Every time a new client booking came in through Google Calendar's appointment scheduler, someone had to manually create a Zoom meeting, copy the details, go back to the calendar invite, and paste in the link for every single booking. One extra step that had to happen reliably every time or the meeting went out without a Zoom link.
After automation: Built a Claude skill that automatically detects new client bookings, creates a Zoom meeting for each one, and updates the calendar invite with the full Zoom details. No manual steps, no missed links. Also runs on a scheduled task so nothing falls through even without a trigger.
Tools/Systems:
I built an interactive brand style guide generator using Claude AI and React that collects business details, analyzes brand personality, and instantly generates complete style guides with color palettes (hex codes included), font pairings, tone of voice guidelines, and visual direction. What used to take 2-3 consultation hours now happens in 5 minutes.
Want to try it? Access the FREE Brand Style Guide Builder here.
Tools/Systems:

Before automation: Manually scoring personality assessments, calculating results, and writing individualized feedback took hours per test making it impossible to scale.
After automation: Built a custom assessment tool using Lovable that analyzes responses in real-time, generates personalized results instantly, and delivers tailored insights automatically. What took hours now happens in seconds.
Take the Core Potential Personality Test here.
Tools/Systems:
Lovable
© jenahflor.com | 2026. All Rights Reserved