The Wiggli Intelligence search engine
An 850M+ profile database paired with AI query interpretation, so you can find candidates without writing complex Boolean strings.
PUBLIC · Feature Overview
Why it matters
Section titled “Why it matters”Traditional search tools make you learn a query language. You guess which job titles candidates use, remember the right operators, and keep adjusting until results look reasonable. It’s slow, brittle, and biased toward what you already know.
Wiggli inverts that. Describe the role in plain language and the engine works out the job-title synonyms, infers the relevant skills, and proposes filters you can adjust. Boolean and manual filters are still there when you want full control. They’re an option, not a requirement.
How it works
Section titled “How it works”The engine sits on 850M+ people profiles and 70M+ company profiles, aggregated from public sources and refreshed in real time. Four ways to start a search:
Smart Prompt
Section titled “Smart Prompt”Type a plain-language description. The engine extracts job title, skills, location, industry, and language, then proposes synonyms you can accept or remove.
Job Description
Section titled “Job Description”Upload a JD (.doc, .docx, .pdf). The engine parses it like a prompt and applies the extracted criteria.
Similar Profile
Section titled “Similar Profile”Upload a CV that represents your ideal hire. The engine finds others with comparable background and skills.
Manual Filters
Section titled “Manual Filters”Build by hand: job titles, companies, exclusions, skills, location radius, industries, schools, certifications, experience, languages, and Boolean.
Once results return, refine with AI-suggested titles, skills, and industries, which surface adjacent terms (and hidden A-tier candidates) you might not have thought of. Exclude irrelevant companies, widen the radius, and save the search as a Saved Filter to re-run later.
A useful split to keep in mind: the search engine finds the pool, the AI Co-pilot qualifies it. Precise, judgment-based criteria (years in a specific field, current vs past role) are better handled by the Co-pilot inside a project than forced into search filters.
When to use which method
Section titled “When to use which method”- New role, clear in your head: Smart Prompt
- New role with a written JD: upload the JD
- “More like this great candidate”: Similar Profile
- Niche role, exact titles and skills known: Smart prompt + Manual Filters or Boolean
Many recruiters seed with a Smart Prompt, then switch to manual to fine-tune. Mixing is normal.
Related articles
Section titled “Related articles”Still stuck?
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