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About the Client

Industry: Recruitment
Location: USA + remote
Team size: 10-49

The client is a recruitment agency that connects global tech companies and startups with C-level executives and senior managers. They focus on providing a high-touch, personalized service in the shortest terms to ensure the best fit and keep up with the competitive market.

recruiter

The Challenge

The recruitment agency struggled to keep pace with the growing volume of data and client demands. They analyzed its operations and identified a critical bottleneck: its manual sourcing process. Their recruiters spent 80% of their work time searching LinkedIn and reaching out to prospects. On average, it took over three weeks to build a strong candidate shortlist for a single position.

That’s why the agency decided to speed up its processes with automation. They wanted to improve and optimize multiple stages of their recruitment workflow, including:

● Sourcing of talent from LinkedIn and other platforms
● Candidate profile analysis for skills and experience matching
● Automation of outreach to candidates through personalized sequences
● Chatbot implementation for initial candidate communication
● Deep analysis of candidates’ skills and CVs before recruiter involvement

Technology
Workflow orchestration

Make.com

Data extraction & enrichment

Phantombuster
Apify

Data management

Airtable

Sourcing & Outreach

LinkedIn
Snov.io

The client needed to level up their service offering and manage more data with limited team resources. The core goal was clear: to provide candidates faster without quality loss.

Before, the agency used LinkedIn for sourcing and Snov.io for outreach. But they lacked the in-house expertise to integrate these tools into an automated workflow.

To solve the uncertainty regarding the tech stack to use, the agency approached DOIT Software for an initial technical consultation. The opportunity to first define the right skill set with the DOIT tech team was the key reason they chose to partner with DOIT for this project. After that, they could immediately access a global pool of automation specialists.

The Solution

DOIT Software analyzed the requirements and recommended the ideal candidate profile for the client's needs. Specifically, the DOIT technical team proposed to look for expertise with these tools:
01
Make.com as a central tool to build the workflow and connect applications.
02
Phantombuster to extract data from LinkedIn profiles (skills, titles, experience).
03
Apify for additional data enrichment.
04
AirTable to store and filter data as a pre-processing layer before triggering Make scenarios. This approach reduces Make credits usage and lowers ongoing automation costs.
05
AI integration to analyze CVs and LinkedIn profiles for experience relevance, skills match, and career consistency.
06
AI for chatbot implementation to connect an LLM API with messaging channels. It enables the system to ask predefined qualification questions and return structured answers to Airtable.

The Hiring Process

With this clear tech stack, the client moved forward with DOIT for the next stage. Since hiring automation specialists is DOIT’s focus area, we maintain a large pre-vetted pool of talent in this domain. Leveraging this network, DOIT immediately began analyzing its Make developers to find the right fit.

 

Our talent matchers sought candidates with a strong technical background and, ideally, experience in similar recruitment tech automation. Besides, DOIT focused on Make developers who had:

 

  • Strong algorithm design and scenario automation skills
  • Experience integrating AI into processes, ability to create and optimize AI prompts
  • Proficiency working with APIs, API testing expertise

Within a few days, the DOIT team presented the shortlist of qualified candidates who met all requirements. Each Make developer went through:

 

  • Recruiter interview with DOIT (30 min)
  • Technical interview with DOIT CTO (40-60 min)
  • Client interview (40-60 min)
  • Project scope evaluation and consultation sessions

During interviews with the DOIT CTO, candidates went through case study analysis and deep technical questions. This stage helped assess their proficiency with the target tools and their problem-solving ability. Based on the results, DOIT narrowed the pool to 5 finalists who were introduced for interviews with the client’s team.

 

The unique part of the selection was a project scope evaluation and consultation sessions with the shortlisted Make developers. Here, they needed to assess the proposed automation architecture and discuss implementation approaches. It was an important extra mile our candidates took to show their technical thinking and domain understanding in practice.

The Results

01

Time to hire: 2 weeks

02

Candidates presented: 5 pre-vetted specialists

03

Interviews conducted: 3 stages + consultation sessions

As a result, the agency successfully hired an experienced Make developer within two weeks.

 

The new automated workflow, built by the DOIT engineer, reduced the time to present qualified candidates from 3+ weeks to less than 1 week. Automated profile extraction, AI-powered analysis, and streamlined outreach eliminated manual bottlenecks. The client also highlighted the quality of the new sourcing workflow, noting that the automation maintains their high standards for vetting.

 

The agency team can now process 3x more profiles than they could with their previous setup. Recruiters spend time on qualified conversations instead of data entry and initial screening.

 

After working together for several months, the recruitment agency is now expanding the role of the hired Automation Engineer to build similar workflow automations for their other departments.

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