What Is Natural Language Search — And How Does It Work?

Allow me to preach to the choir for a second: 

For years, the task of sourcing talent has relied on a form of communication that feels more like code than conversation: Boolean strings. Recruiters have become adept at crafting complex queries using AND, OR, and NOT, but this process is slow, tedious, and often leads to missed opportunities.

Even experienced recruiters spend valuable time tweaking searches. It’s a method that often feels rigid and unforgiving, excluding great candidates who don’t perfectly match a narrowly defined set of keywords or filters.

But what if you didn’t have to speak a machine’s language to find the right person for the job? What if the machine could understand yours? (A novel concept, right?) This is the core principle of Natural Language Search (NLS), and it's fundamentally changing how recruiters source talent.

How Natural Language Search works

Natural Language Search allows you to type what you want in plain, conversational language. Instead of building a query like:

("Software Engineer" OR "Software Developer") AND (Python AND Java) AND "San Francisco" AND (startup OR "early stage")

You can simply write:

"Find a senior software engineer with experience in Python and Java, located in San Francisco, who has worked at a startup".

Behind the scenes, the AI uses sophisticated technology to interpret your request. It doesn't just look for exact keyword matches; it understands the intent, nuance, and related context of your query. 

For example, the system knows that "software developer" is a related term for "software engineer," and it can automatically expand your search to include both. This context-aware approach dramatically reduces the risk of overlooking qualified candidates.

This is a stark contrast to traditional Boolean and keyword searches that struggle to capture intent — and thus often miss candidates who use different terminology to describe their skills. 

For example, a recruiter searching for "Project Manager" and "Agile" with Boolean might miss a perfect candidate who lists "Scrum Master" and "iterative development" instead. NLS, however, understands the relationship between these terms and can surface both.

The best part? You can use NLS as a starting point, and then refine your search with Boolean and filters to drill down your results and build the strongest possible longlist. So you don’t need to throw the Boolean baby out with the bathwater — instead, you can use it more strategically. 

The power of integrated AI

The real power of a tool like NLS is when it's fully integrated into your existing platform. This allows you to search both your own internal database and a broader network of professional profiles at the same time, without switching tools. The system does the heavy lifting upfront, allowing you to quickly cast a wide, context-aware net and then refine the results with filters or Boolean as needed.

Expanded talent pool

NLS uncovers candidates you might otherwise miss with rigid filters or manual Boolean searches, ensuring you capture the widest pool of qualified candidates that match your intent.

Standardized quality

It allows recruiters of any skill level — from a new hire on day one to a seasoned pro — to source effectively and consistently, leveling the playing field across your team.

Faster, more focused work

By eliminating the tedious work of crafting complex strings, recruiters can spend less time tweaking queries and more time engaging with qualified talent. This accelerates time-to-first-submittal and helps you beat competitors to top talent.

The future of recruitment isn’t coming — it’s here 

The market has long been challenged by the slow, inconsistent, and often frustrating nature of traditional sourcing methods. Boolean takes time and skill to master, while rigid filters can exclude great candidates who don't fit perfectly. These issues create a sourcing bottleneck, leading to inconsistent results and missed opportunities.

Natural Language Search was built to remove these barriers. It's a key part of the larger vision for the future of recruiting, where technology works for the recruiter, not against them. By making sourcing faster, more consistent, and more comprehensive, NLS empowers recruiting teams to focus on the human side of their work — building relationships, engaging with candidates, and making great matches.

The future of recruiting software isn't on the horizon; it's already here, and it’s conversational, intelligent, and designed to help every recruiter source like a pro from day one.