Find talent faster and easier with Greenhouse Talent Filtering and Talent Rediscovery

3 mins, 9 secs read time

Finding top-notch candidates faster and more efficiently isn’t a nice-to-have for most companies – it’s a necessity. That’s why our Greenhouse R&D team reimagined candidate sourcing to help transform your Greenhouse database into your most valuable sourcing tool.

The result? Talent Finder V2, a game-changing project that simplifies sourcing with two new features:

• Talent Filtering (Launched August 2024)

• Talent Rediscovery (Launched December 2024)

Let’s explore how these tools solve your sourcing challenges and help you quickly find talent that will make a big impact at your organization.

Filter out the noise: Identify the right applicants for your roles with Talent Filtering

Solving the high-volume problem

Whether from new economic trends or the recent influx of AI resumes, high application volumes can overwhelm even the most seasoned recruiters. This can make identifying the right candidate difficult, time-consuming – and let’s admit – a little soul-crushing.

Manual application reviews consume valuable time that hiring teams could better use for strategic tasks. Alternatively, recruiters may be overly dependent on AI to make sourcing decisions for them. This can lead to qualified candidates being overlooked by undetected biases in algorithms.

Introducing Greenhouse Talent Filtering

Talent Filtering uses AI to simplify application review and find talent without compromising hiring teams’ transparency or control. It can help you identify the right applicants by:

• Automatically suggesting AI-generated keywords based on the job description or your chat interface input

• Searching both resumes and internal notes on candidates to surface a complete list of search results

• Offering candidate filters tailored to your team’s unique Greenhouse data (e.g. Only show internal candidates, Only show referrals, Candidate tags)

Unlike tools that rank candidates via opaque algorithms, Greenhouse Talent Filtering empowers humans, not AI, to make application review decisions with efficiency, confidence and clarity.

Get a head start: Turn your existing database into a top source for candidates with Talent Rediscovery

Solving the database problem

When hiring teams open new jobs, they often start from scratch with empty pipelines, even though their databases are full of candidates they have engaged with before (sometimes hundreds of thousands!). The problem? Many systems make it hard to surface past talent. As a result, companies turn to pricey third-party AI sourcing tools that increase costs and complicate tech stacks.

Introducing Talent Rediscovery

The new Greenhouse Talent Rediscovery feature helps companies reconnect with high-potential talent – no costly supplemental tools required.

It can help you find potential candidates from within your own database by:

• Automatically suggesting AI-generated keywords based on the job description or your chat interface input

• Offering candidate filters that are tailored to your team’s unique Greenhouse data (e.g. past interviewing activity)

• Capitalizing on the way you’ve already organized and segmented your prospect database in CRM (e.g. filter by prospect pool and stage)

• Driving efficiency by letting you save and reuse searches or grouped filters

Talent Rediscovery helps you work smarter, not harder, and transforms your Greenhouse database into a powerful talent source. Whether you’re interviewing and submitting scorecards, advancing or rejecting candidates or organizing your CRM, Talent Rediscovery will help get you closer to making great hires for today and beyond.

What’s next?

We can’t wait to see how these enhancements take your sourcing (and your business) to the next level and look forward to your feedback. We’ll continue innovating to help customers find that next hire even faster – stay tuned!


If you’re ready to get started, check out these Talent Filtering and Talent Rediscovery Greenhouse support articles, or see our latest releases and features here.

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