At a Glance: A Denver-based HRTech startup at $6M ARR needed to rebuild their hiring platform dashboard with AI-powered candidate insights. Second Talent placed 3 senior React engineers in the Philippines within 4 weeks, providing full EOR services. The team shipped the AI insights feature in 5 weeks while cutting dashboard load times by 60%.
The Challenge
The company had a problem. Their hiring platform dashboard was slow. Customers complained about 8-second load times when reviewing candidate profiles. User satisfaction scores sat at 52%. They were losing deals to competitors with faster, AI-enhanced platforms.
The technical debt was significant. Their dashboard ran on an outdated React setup with no TypeScript. Real-time updates required full page refreshes. The engineering team knew they needed a complete rebuild with Next.js, proper typing, and WebSocket integration for live data. They also wanted to integrate AI-powered candidate insights to stay competitive in 2025.
Local hiring in Denver was not working. Senior React engineers with TypeScript and Next.js experience commanded $160K to $180K annually. The company interviewed 12 candidates over 3 months. Only 2 had the specific skill set they needed. Both declined after receiving counteroffers. The VP of Engineering had 8 weeks to ship the AI insights feature before a major industry conference where they planned to announce it.
They needed engineers who could work with AI tools to accelerate development. The rebuild would involve integrating multiple AI APIs for resume parsing, skill matching, and candidate scoring. Traditional developers would take 4 to 5 months for this scope. They did not have that time. They needed AI-native engineers who could use Claude, Cursor, and GitHub Copilot to compress timelines while maintaining code quality.
The Solution
Second Talent presented 8 qualified candidates within 10 days. All were senior React engineers with 6+ years of experience. All had production experience with TypeScript, Next.js, and WebSocket implementations. All were AI-native developers who used AI coding assistants daily. The company interviewed 5 candidates and selected 3 within 2 weeks.
The developers were based in the Philippines. Second Talent handled all EOR services including payroll, benefits, compliance, and local tax requirements. The setup took 6 days. The company paid a single monthly invoice. No entity setup. No local HR headcount. No compliance risk.
Each developer cost $5,800 per month. Total monthly cost for 3 developers was $17,400. Equivalent talent in Denver would have cost $45,000 monthly at minimum. The 65% cost savings gave the company budget flexibility to invest in AI API costs and additional tooling.
The team integrated immediately. They worked 4 hours of overlap with Denver time. Daily standups happened at 8am Mountain Time. The developers used Cursor and GitHub Copilot to accelerate the Next.js migration. They used Claude to generate TypeScript interfaces from API documentation. Code review cycles dropped from 2 days to 4 hours because AI tools caught most issues before human review. The VP of Engineering reported that PR quality was higher than their previous US-based contractors.
The Results
The AI insights feature shipped in 5 weeks. The team rebuilt the entire dashboard in Next.js with full TypeScript coverage. They implemented WebSocket connections for real-time candidate updates. Dashboard load times dropped from 8 seconds to 3.2 seconds, a 60% improvement. User satisfaction scores jumped from 52% to 73%, a 40% increase.
The AI-powered candidate insights became their top differentiator. The feature used GPT-4 to analyze resumes and generate skill match scores. It provided hiring managers with AI-generated interview questions based on candidate backgrounds. Customers using the AI insights hired candidates 35% faster than those using the old dashboard. The company featured the new dashboard at the industry conference and closed $1.2M in new contracts within 30 days.
Development velocity stayed high after launch. The team shipped 47 feature updates in the first 90 days post-launch. Bug reports dropped 58% compared to the old platform. The developers used AI tools to write comprehensive test coverage, reaching 84% code coverage compared to 31% on the legacy system. The VP of Engineering calculated that AI-assisted development made each developer 2.3x more productive than traditional development approaches.
Key Outcomes
- Performance Gains: Dashboard load times decreased from 8 seconds to 3.2 seconds, a 60% improvement that directly impacted user satisfaction scores, which rose from 52% to 73%.
- Accelerated Time to Market: The team shipped the AI-powered candidate insights feature in 5 weeks instead of the projected 16 weeks, enabling the company to announce it at a major industry conference and close $1.2M in new contracts.
- Cost Efficiency: The company saved 65% on engineering costs compared to Denver hiring, paying $17,400 monthly for 3 senior developers versus $45,000 for equivalent US talent, freeing budget for AI API costs and tooling.
- Quality and Velocity: AI-native development practices resulted in 84% test coverage, 58% fewer bug reports, and 2.3x productivity gains per developer, with the team shipping 47 feature updates in 90 days post-launch.
“We needed senior React talent fast, and Second Talent delivered in under 3 weeks. The developers were AI-native, which cut our development time in half. We shipped our AI insights feature in 5 weeks and saw immediate customer impact. The 65% cost savings let us invest more in product instead of overhead.”
VP of Engineering
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