---
title: "HireDash: AI résumé screening and ranked shortlists | FLUIDS"
description: "HireDash helps hiring teams turn PDF résumés into a ranked shortlist. It compares candidates with role requirements and shows fit scores with written reasoning for human review."
url: https://fluids.studio/work/hiredash
language: en
---
SaaS

# HireDash

An AI résumé-screening product — upload PDFs and review a ranked shortlist with reasons.

Read the product story and workflow

![HireDash — An AI résumé-screening product — upload PDFs and review a ranked shortlist with reasons.](https://fluids.studio/lovable-uploads/HireDash.webp)

## HireDash: the product and how it works

HireDash helps hiring teams turn PDF résumés into a ranked shortlist. It compares candidates with role requirements and shows fit scores with written reasoning for human review.

On this page

- Screen applicants against the role you are hiring for
- From PDF uploads to an explained shortlist
- Keep useful applicants available for future roles
- Product questions

### Screen applicants against the role you are hiring for

A folder of résumés leaves a recruiter repeating the same checks: required skills, relevant experience, languages and education. A keyword match alone does not explain whether a candidate meets the role’s requirements.

HireDash starts with the role. The hiring team defines requirements and scoring priorities, or uses a job description to draft them with the AI role builder. The draft remains editable before any résumé is screened.

### From PDF uploads to an explained shortlist

The team uploads PDF résumés for a selected role. HireDash extracts structured candidate information and compares it with the role. Results include a fit score from 0 to 100, a written summary and a requirement-level breakdown.

Custom extraction questions let the recruiter ask the same additional question across candidates, using answer types such as yes/no, a number, a category or a short summary. These checks make the screening brief more explicit. Scores and generated explanations are decision support; the team still needs to check the evidence and decide who progresses.

### Keep useful applicants available for future roles

Processed candidates become part of a searchable talent pool. When a different role opens, the team can re-analyse a past candidate against the new requirements. A candidate who was unsuitable for one vacancy may be relevant to another.

An in-product assistant answers questions using the team’s roles, candidates and analysis results. FLUIDS designed and built HireDash as a hiring workflow product: role definition, résumé processing, review and reuse of the candidate pool belong to the same experience.

### Questions about HireDash

**Is HireDash a job board?**

Its documented workflow focuses on screening résumés supplied by the hiring team, ranking applicants and reusing a candidate pool.

**Does HireDash explain the fit score?**

Yes. The fit score comes with written reasoning and a breakdown against the role’s requirements.

**Does the AI make the hiring decision?**

The product presents scores, summaries and requirement checks for review. The hiring team makes the decision.

**Can past applicants be assessed for a new role?**

Yes. The talent pool supports re-analysis of a candidate against a different role.

### Related products

- [Leadify](https://fluids.studio/work/leadify)
  An AI lead-generation platform for Saudi Arabia and the Gulf — describe a customer in plain language, and get a verified lead list.
- [Oxygen Academy](https://fluids.studio/work/oxygen-academy)
  A university-aligned EdTech platform for Saudi students — courses, exams, and AI study tools in one place.

### Need a similar product?

- [SaaS product development](https://fluids.studio/saas-development)
- [AI features inside your product](https://fluids.studio/ai-features)
- [Visit HireDash](https://hiredash.org/)

## Guides from building this product

What we learned building HireDash, written up as practical guides for anyone planning a similar product.

- [AI résumé screening: how it works, from PDF upload to ranked shortlist](https://fluids.studio/blog/ai-resume-screening)
- [Explainable candidate scoring: why a fit score needs written reasons](https://fluids.studio/blog/explainable-candidate-scoring)
- [Reusing your talent pool: re-analysing past applicants for new roles](https://fluids.studio/blog/talent-pool-reanalysis)
- [ATS or a custom AI screening tool? How to decide](https://fluids.studio/blog/ats-vs-custom-hiring-tool)
- [Fair AI hiring: human review, bias checks and candidate data](https://fluids.studio/blog/ai-hiring-human-review)

[All guides on the blog](https://fluids.studio/blog)