Client Implementations
Real work, anonymized by default. Each entry below reflects an actual engagement — problem, solution, and outcome. Case studies publish once results are validated.
Results verified before publishing
SaaS, Human Resources, Job Boards, Head Hunters
1-10VerifiedButterfly Resume
Problem
- Resumes don’t match the job posting. Good experience gets overlooked because it’s not framed in the language recruiters/ATS scan for.
- AI resume tools create trust risk. Many tools embellish or “fill in gaps,” leading to misrepresentation and interview anxiety.
- Transferable skills are hard to translate. People struggle to connect past roles to a new domain without accidentally claiming things they didn’t do.
- Applicants don’t know what they’re missing. Most tools don’t clearly flag unmet requirements or what to do next.
- Rewriting is repetitive. Users waste time recreating slightly different versions of the same resume.
Solution
- Build once: Import resumes/LinkedIn into a canonical, editable truth profile (roles, bullets, skills).
- Prove everything: Every bullet ties to evidence (snippets + optional evidence URLs).
- Tailor safely: Parse job posts, match requirements to proven bullets, and generate ATS-safe exports.
- Approval gate: Any “transferable inference” suggestion is flagged and requires explicit user approval before export.
- Gap Checklist: Unmet requirements are highlighted with honest substitutes and quick next steps.
Outcome
- Higher job-fit clarity: Resumes read like they were written for the posting—without lying.
- Reduced interview risk: Users can defend every line with evidence and confidence.
- Faster applications: Generate multiple job-specific exports from a single profile.
- Actionable direction: Users see exactly what’s missing and what to improve next.
- Enterprise-ready foundation: Auditability (Evidence Map + approvals) is built in from day one.
Next.js, TypeScript, Tailwind, Supabase, Claude, ChatGPT