Built an AI-powered lead enrichment and CRM automation platform designed to help sales teams identify high-quality prospects, enrich lead data automatically, and streamline outreach workflows.
The platform combines AI, external data sources, CRM systems, and workflow automation to reduce manual research while improving lead quality and sales efficiency.
Key Features
• Automated lead enrichment
• Company and contact research
• AI-generated personalized outreach emails
• CRM synchronization
• Lead scoring system
• Sales pipeline automation
• Contact validation
• Automated follow-up workflows
• Multi-source data aggregation
• Analytics and performance tracking
Business Impact
✓ Reduced manual lead research
✓ Increased sales team productivity
✓ Improved lead quality
✓ Faster prospect qualification
✓ Higher outreach efficiency
✓ Better CRM data accuracy
✓ Increased pipeline visibility
Technology Stack
• Java
• Spring Boot
• PostgreSQL
• OpenAI API
• REST APIs
• CRM Integrations
• Workflow Automation
• Analytics Dashboard
Results
• Reduced lead research time by approximately 80%
• Automated prospect enrichment process
• Improved CRM data quality
• Increased sales team efficiency
• Faster lead qualification workflows
This solution demonstrates how AI can automate prospect research, improve lead quality, and accelerate sales operations.
An AI marketing automation experience designed around the needs of marketing teams, growth marketers, and digital businesses.
The interface brings campaign management, customer journeys, analytics, and AI-driven optimization into a focused SaaS product experience, making complex automation easier to understand and navigate.
B2 English, based in Argentina. Payment preferably in USDT. Remote only. Quite a combination, right?
I built an AI-assisted job-search system around Freehire and Hirify. Both platforms offer official API/CLI access for automation, which makes them much easier to connect to an agent workflow. Simple Python scripts collect job listings and run the first pass of filtering against strict rules.
Then agents double-check the requirements, match them against my experience, and tailor my CV to each role. They highlight relevant projects and technologies I've actually worked with. Final review and approval stay with me.
𝐀𝐬 𝐨𝐟 𝐒𝐞𝐩𝐭𝐞𝐦𝐛𝐞𝐫 𝟐𝟔:
✅ 20 applications sent;
✅ 8 HR screenings passed;
✅ 1 video screening completed and submitted.
🚀 Technical interviews are still ahead.
I'm not ready to write off the market. Even with my constraints, things are moving.
A job search deserves 𝐚𝐧 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 𝐭𝐨𝐨: clear rules, automation, and checks on the results.
Normal work disappears. Genuine judgment surfaces.
I built Northline Flow for @Lovable’s #lovablechallenge — a fictional owner-operated home-services business in Surrey, BC.
I didn’t want to build another prettier scheduler. The problem I wanted to attack was the handling around the booking.
Routine requests can continue toward booking. Genuine ambiguity reaches the owner as one framed decision. Unsafe or wrong-fit requests stop instead of being forced into the normal booking path.
I also built a deterministic test harness and a playable Morning Shift proof mode: three fictional requests enter the same routing rules, but only one requires a human decision.
The part I’m most excited about is that the challenge itself became reusable. We captured the process from brief → working flow → adversarial testing → cinematic donor → bounded visual integration → playable proof → final freeze.