FAQ

What is DINQ?

DINQ is an AI talent discovery engine that helps recruiting teams find, organize, and research candidate leads from multiple public sources.

You can describe the person you are looking for in natural language. DINQ organizes information from public professional profiles, GitHub, Google Scholar, papers, projects, personal websites, technical communities, and other public sources into candidate profiles that are easier to review, evaluate, and contact.

How is DINQ different from LinkedIn?

LinkedIn is primarily a professional networking platform where people present their roles, work history, and professional connections. DINQ is a talent discovery engine that helps you search across public work signals such as GitHub, papers, projects, personal sites, and technical community activity.

DINQ helps recruiters review public evidence of a candidate's work in one sourcing workflow.

How is DINQ different from GitHub Search?

GitHub Search is designed to find repositories, code, issues, and developers within GitHub. DINQ is designed for talent discovery across multiple public sources. It can combine GitHub signals with sources such as publications, professional profiles, personal websites, and technical communities, then organize candidate profiles for review.

I already use LinkedIn and GitHub. Why do I need DINQ?

You can use LinkedIn, GitHub, Google Scholar, and other public platforms manually. DINQ brings those steps into one workflow: discover candidates, review profiles, save shortlists, and contact candidates with context.

Which roles is DINQ best suited for?

DINQ is especially useful for roles where resumes alone do not fully capture experience or ability, such as AI, ML, infrastructure, quantitative finance, security, robotics, biotech, research, medical technology, and other fields where projects, papers, code, or public contributions matter.

How does DINQ search work?

DINQ uses an AI-assisted, multi-source search workflow. You can enter a natural-language request or upload a job description. DINQ interprets the search goal and may ask follow-up questions to refine criteria such as location, experience level, education, compensation range, and number of candidates.

Why does a DINQ search take time?

DINQ is not simple keyword matching. It searches across sources, organizes information, matches candidates, and provides source links where available. This can take time, but it helps create more structured and reviewable candidate leads.

Are DINQ search results always accurate?

No. DINQ is a tool for expanding search, organizing clues, and supporting candidate research. Search results, Match Scores, and AI-generated summaries should be used as reference information, not final hiring decisions.

How does DINQ generate candidate profiles?

DINQ organizes relevant information from public sources, such as professional profiles, education, project experience, open-source contributions, papers, personal websites, and technical community activity.

These profiles should be treated as collections of candidate leads and signals, not final evaluations.

What are DINQ AI insights?

DINQ AI insights are AI-assisted summaries and analyses generated from public-source information. They help you understand how a candidate may relate to a search request.

You should review source links and apply your own hiring criteria before making decisions.

How does DINQ handle sources and verifiability?

DINQ aims to provide source links for candidate profiles, recent activity, projects, papers, and other public signals where available.

Users should independently assess and verify important information before relying on it in a hiring process.

Is a Profile public?

Yes. A Profile is public and may be accessed, indexed, cached, or archived by users, visitors, search engines, or third parties.

Only add information to your Profile that you are comfortable making public.

Where can I learn more about data and privacy?

See Data & Privacy for information about public data sources, Profile visibility, private workspace data, AI processing, and account data controls.

Can DINQ replace human hiring judgment?

No. DINQ is an AI-assisted sourcing and candidate research tool. It does not replace the professional judgment of recruiting teams and should not be used as the sole basis for automated hiring, rejection, or ranking decisions.

What should users keep in mind when contacting candidates?

Use your real identity and communicate professionally, respectfully, and transparently. Avoid harassment, spam, or misleading messages.

If you use AI-generated outreach, review and edit the message before sending it.

Does DINQ automatically decide who is suitable for a role?

No. DINQ helps users discover candidates, organize public information, generate AI-assisted analysis, and provide relevance signals. Final hiring judgment should be made by the user and their recruiting team.

What are users responsible for when using DINQ?

Users are responsible for using DINQ in a lawful, respectful, and professional way. This includes reviewing important information before relying on it, communicating transparently, avoiding spam or misleading outreach, and following the privacy, employment, and candidate communication rules that apply to their jurisdiction.