Speed up research & outreach with TechTree's AI Agent

Make it easy for your team to source and engage candidates by giving them access to AI agents powered by detailed candidates data.

What people saying about TechTree

Conrad Wadowski
Founder at Kick

"Our experience with TechTree and its data-driven recruitment platform has been incredible. We worked closely together to make a staff-level hires with backgrounds in Nvidia, Meta and Box. We're continuing to work together and highly recommend."

Jan Philipp Hass
CEO of stealth AI company

"We started to work with TechTree while being in stealth looking for our first hires. Their AI agent approach proved to be innovative and effective - we interviewed over 90% of candidates they shared. Thanks to them we have now hired an ex Github founding engineer with a true passion for the specific problem we're solving."

Vlad Galu
Founder & CTO of Refute

"We used TechTree to make our first 2 hires. We loved the experience with their product that enabled us to very precisely set and adjust the criteria and reach out to people directly from our account and get a great response rate. Over 80% of people shared with us was invited to the interview process, which gave us a great choice."

How it works:

Step #1

Input

Simply chat with our AI agent to pinpoint your ideal candidate profiles—just describe the type of people you're looking for, and our AI will do the rest.
Step #2

AI Research

The AI agent automatically generates a market map for your target profile, analyzes professional profiles and 100s of data points in real time, and shortlists the most relevant candidates.
Step #3

Automated reach out

Connect your LinkedIn to run automated outreach.
Step #4

Make more placements

Super granular AI Research results

To meet the sophisticated of hiring companies we’ve integrated data from multiple sources, including
+ LinkedIn
+ Detailed company info (funding, headcount, investors)
+ Academic track record
+ career details - tenure length, promotions

We've also developed new, high-signal metrics by connecting fragmented data sources. Examples include:
+ Career stage at specific companies
+ Candidates who worked at companies backed by specific investors
+ TechTree score: a talent quality score based on multiple factors.

Example of Data Points:

Investors

The caliber of investors who supported the companies where an individual worked.

Stage Experience

The funding stage that companies were in during the candidates' tenure there.

Employment Data

The titles, tenures, promotions, job category, seniority, etc.

Change Logs

Any changes made to their LinkedIn to indicate intents (job search, founding, etc)

TechTree Score

Proprietary career weighting score (promotions, tenures, investors, etc).

Context Skills

Insights by interpreting information through its context and environment.

Shared Connections

The shared work history of your network, enabling you to find the best intro route.

And more...

Any publicly available
data point

Looking to talk to someone?

Book a demo