HR & recruiting technology
We ship an AI ATS. That changes how we build yours.
Vision Nexera designs, builds, and operates NexeraHR, a production AI applicant tracking system. Every parsing decision, every matching heuristic, every screening workflow gets stress-tested on our own product first. That is why we get called for the hard hiring-tech problems: we have already lived with the answers.
What we hear
Four problems every hiring-tech team runs into
These are the conversations we have every month with founders, HR platforms, and internal talent teams building on top of AI.
Resumes arrive in every shape
Two-column layouts, scanned PDFs, five date formats, job titles that mean different things at different companies. A pipeline that only handles the well-formatted majority quietly discriminates against everyone else.
Recruiters drown in unstructured data
Screening across inboxes, spreadsheets, and half-configured ATS tools burns the hours that should go into candidates. The bottleneck is turning chaos into comparable structure, reliably.
Hiring decisions are legally sensitive
Bias, adverse impact, and audit questions are not marketing risks; they are legal ones. AI in hiring must assist screening with humans on the decisions, by design, not as a disclaimer.
Enterprise ATS pricing exists
The good tools were priced and designed for enterprise procurement cycles. SMB and mid-market teams either overpay or build workarounds that leak time daily.
What we build for this industry
Six things we have shipped, more than once
Resume parsing pipelines
Schema-first extraction, LLM where judgment wins, deterministic rules where correctness must be exact, with every human correction becoming a permanent evaluation fixture.
Candidate matching & ranking
Structured profiles ranked against role requirements with reasoning visible to recruiters, so “why is this candidate #3?” always has an answer that stands up in a meeting.
Screening workflows
Stages, decisions, and interviewer feedback captured as records (not lost in an inbox) with human gates exactly where hiring decisions get made.
Attendance & hardware integrations
Biometric devices (ZKTeco), calendar, and HRIS integration engineered as resilient adapters, because messy hardware protocols meet clean APIs at the boundary you own.
Compliance-grade payroll rules engines
Statutory rules encoded as versioned, effective-dated code: testable, auditable, and updatable when regulations change. Payroll is legislation as arithmetic; treat it that way.
AI-native candidate-facing UX
Streaming outputs, tailored artifacts, and honest “still working” states: the interface layer that makes AI features feel engineered, not bolted on.
Proof
What we actually run in this industry
NexeraHR: an AI-powered ATS we design, build, and operate
Resume parsing, candidate matching, and screening workflows for SMB hiring teams, in production, run by the team that built it.
Case study →
Client workRocketJob: an AI job-search platform and application service
A resume-tailoring engine with versioning and pixel-faithful PDF output, a content platform built for search, and a human-in-the-loop application service, engineered by Vision Nexera for RocketJob.
Case study →
Deeper reading
Inside NexeraHR's resume-parsing pipeline
Resume parsing looks like a solved problem until you meet real resumes: two-column layouts, five date formats, job titles that mean different things at different companies. Our pipeline gets reliability from three decisions: a strict output schema, rules where determinism wins, and every human correction becoming a permanent test case.
Next step
Bring the hiring-tech problem to the people who run one.
Thirty minutes with the engineers behind NexeraHR. You leave with a written scope, an honest estimate, and our view on whether AI is even the right tool.
Prefer async? hello@visionnexera.com · We reply within one business day.