Case Studies
Systems I've built. Results they deliver.
Not mockups. Not proposals. Working infrastructure running in production right now.
Automated B2B Lead Generation Pipeline
Problem: Sales team had no time for cold outreach. Prospecting, list building, and personalization were falling through the cracks.
What I built: End-to-end pipeline that monitors industry news for buying signals, discovers companies, enriches contacts via APIs, runs them through a 7-gate quality filter, generates personalized outreach with AI, and enrolls qualified leads into sequences automatically.
Results
- 20-50 pre-qualified leads enrolled per week, fully autonomous
- ICP filtering catches the majority of poor-fit contacts before they waste outreach slots
AI-Managed Executive Calendar
Problem: Executive calendar management was entirely manual. Daily planning, meeting prep, focus blocks, conflict checks, and family coordination all fell on one person.
What I built: Dedicated AI calendar assistant with its own account. Handles daily planning, generates morning briefs, prepares meeting context, manages recurring events, detects conflicts, and syncs across work and personal calendars.
Results
- 4-5 hours/week saved across planning, prep, and coordination
- Nothing gets scheduled without human confirmation
LinkedIn Network Analysis
Problem: Thousands of connections accumulated over years with no way to identify high-value contacts, segment by industry, or prioritize outreach.
What I built: Automated pipeline to import, clean, deduplicate, and score all connections. Segmented by decision-maker status, industry, and outreach potential.
Results
- Over 80% of manual categorization work eliminated
- ~17% of connections identified as decision makers
- Contacts categorized, triaged, and ready to feed into outreach workflows
Daily Industry Intelligence Digest
Problem: Staying current across 16+ news sources, blogs, and forums took 30-45 minutes per day of scattered browsing.
What I built: Automated pipeline that fetches RSS feeds, deduplicates articles with fuzzy matching, summarizes each with AI, and delivers a formatted digest to the team chat every morning at 8am.
Results
- 3-4 hours/week saved on manual news monitoring
- 15-30 curated articles per digest, filtered for relevance
Rapid Prototype: Lead Generation Dashboard
Problem: Team depended on manual processes to configure ideal customer profiles and manage prospecting. No central interface, and no way to align stakeholders on what the solution should look like.
What I built: Instead of weeks of back-and-forth, I built a working web dashboard in two hours to showcase what the project would look like. Configured for ICP management, lead searches, and pipeline filtering. Demoed live to stakeholders to validate the concept before committing resources.
Results
- Working prototype built in two hours
- Stakeholder alignment achieved in a single demo
Tool and Release Monitoring
Problem: Keeping track of software releases, updates, and trending tools across multiple sources required checking several pages multiple times a day.
What I built: Hourly automated scan of release feeds and trending repositories, filtered by relevance, deduplicated, summarized by AI, and posted to a team channel.
Results
- 1-2 hours/week saved
- Catches overnight and weekend releases automatically
- Filters out noise: only surfaces meaningful changes
CRM Data Cleanup and Structuring
Problem: CRM database had grown organically over time. Loose information, inconsistent records, duplicates, and no clear structure made it hard to trust the data or act on it.
What I built: Audited the full database, identified data quality issues, deduplicated records, standardized fields, and restructured the data so every contact and company record was clean, consistent, and actionable.
Results
- Entire database cleaned and restructured
- Duplicates and inconsistencies eliminated
- Clean data foundation for all downstream automation
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