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.

Where can I use DINQ?

Visit the DINQ product website, open talent search, or read the official help center at docs.dinq.me. Recruiters and hiring managers can use search, shortlists, and email outreach; researchers can explore advisor matching, citations, and talent analysis; developers can connect through the API or MCP. Some features require sign-in, access permissions, or available Credits.

Which sources are available?

The DINQ website describes coverage of 500+ data sources, including GitHub, academic publications, patents, and professional networks. Availability for a particular request depends on its entry point, task, permissions, and service state; this is not a promise that every source is searched on every run. Use dinq_capabilities for available MCP platforms and see API for supported source parameters.

How is DINQ different from LinkedIn?

DINQ connects natural-language requests, cross-source research, public-work verification, shortlists, and email outreach into a sourcing workflow. A public LinkedIn profile can be one source, alongside code, papers, and projects.

Use DINQ to organize those clues, then open original sources to verify important details. This describes DINQ's workflow, not a complete comparison of other products' current features or plans.

How is DINQ different from GitHub Search?

DINQ can organize GitHub code, projects, and contributions alongside publications, professional profiles, and personal sites into candidate results for review, shortlisting, and outreach. Open the original GitHub links when verifying specific code or contributions.

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 interprets a natural-language request or uploaded reference file and prepares an editable Search Plan. Review the objective, Must / Prefer / Exclude criteria, optional questions, and requested count, then start searching. Text, PDF, images, TXT, Markdown, CSV, and DOCX are supported as described in Input Methods.

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.

Are profile generation and email lookup one charge?

No. Each successful new search-page profile costs 5 Credits, and each successfully resolved candidate email lookup costs 20 Credits. Search itself also has usage charges. See Pricing & Credits for cached reuse, regeneration, and bulk actions.

Why does a team request fail when I have personal Credits?

Personal and team spaces have different usage contexts. Check the selected space, team balance, and your member monthly cap, then contact Owner or Admin. Switching spaces does not transfer personal Credits into the team.

Can a search continue after I leave the page?

DINQ attempts to restore searches still running in the background. Reopen the history conversation and check its state before starting a duplicate request. Stopped, failed, or inaccessible sessions are not guaranteed to resume. See Search History.

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.