Reduce bad AI resume matches with iterative prompt optimization

Reduce bad AI resume matches with iterative prompt optimization targets a $48.0B = 3,000,000 companies x $16,000 ACV (enterprise HR tech + matching spend) total addressable market with medium saturation and a year-over-year growth rate of 12% (HR tech / talent acquisition automation growth).

Key trends driving demand: LLM comprehension -- large models now capture semantic skills and role-context, enabling better match scoring beyond keywords; Skills-based hiring -- employers focus on skills over credentials, increasing demand for semantic parsing and rewriting; Automation of sourcing/screening -- cost-per-hire pressure pushes teams to adopt AI tools that measurably reduce time-to-hire; Privacy & compliance tooling -- improved enterprise data controls make integrations with candidate systems safer and more acceptable.