At ProDevs, we believe in creating opportunities for African tech talent by connecting them with global opportunities. Over the past year, we’ve witnessed unprecedented growth in our talent pool. More developers, designers, and product managers are joining our platform every day, seeking remote roles that align with their skills and aspirations.

However, with this growth came a challenge—how do we efficiently vet this influx of talent without compromising on quality? Our recruitment team was swamped with profile reviews. As we scaled, we knew we couldn’t rely solely on our semi-automated vetting process. We needed to find a way to maintain our high standards while keeping up with demand.

This is the story of how we deployed an AI agent that transformed our vetting process and reduced our vetting time by 80%.

The Growing Challenge

When ProDevs started, our vetting process was simple yet effective. We used a combination of manual reviews and automated checks to evaluate talent profiles. Our team looked for unique data points—skills, project experience, certifications—that would help us isolate exceptional talent from the rest. This semi-automated approach worked well at first.

But as our platform grew, the volume of profiles skyrocketed. Our recruitment team found themselves overwhelmed, spending hours reviewing profiles. The need to vet new talent alongside re-vetting existing talent became a bottleneck. We knew that if we didn’t solve this challenge, we risked slowing down our mission of connecting African talent with global opportunities.

We needed a solution that would:

• Reduce vetting time

• Maintain or improve accuracy

• Scale with our growing talent pool

Enter AI.

Our First Attempt: Training an AI Model with Historical Data

Our initial approach was to train an AI model using the GPT-3.5-turbo model. We fed it historical data from our platform—profiles we had reviewed and classified over time. The idea was simple: the AI would learn from past vetting decisions and help us automate the process.

At first, the results seemed promising. The AI was able to categorize profiles and provide insights at a much faster pace than our human team. But as we tested it further, we realized a glaring issue—the accuracy rate was around 79%. That might sound good, but for us, it wasn’t enough. We couldn’t afford to risk presenting clients with less-than-stellar candidates.

Why the low accuracy? The problem wasn’t with the AI itself—it was with the data we had used to train it.

Our historical data contained inconsistencies. Human reviewers had made mistakes. Different reviewers had different standards. And those errors were now baked into the AI’s training data.

We realized that to build a reliable AI model, we needed to start from a clean slate. We needed a standard.

Creating a Standard: The Talent Frameworks

To solve the accuracy issue, we went back to the drawing board. We developed a series of Talent Frameworks that outlined the key competencies, skills, and responsibilities expected at different career levels across various roles—from software engineers to product designers to DevOps professionals.

These frameworks became our new gold standard for vetting. Instead of relying on subjective judgments, we now had clear, objective criteria for evaluating talent.

With these frameworks in hand, we retrained our AI model. This time, the AI wasn’t just learning from past decisions—it was learning from a set of well-defined standards.

The difference was night and day.

The Impact: Immediate and Transformational

Once we deployed the new AI agent into our platform, the impact was felt almost immediately:

• Vetting time dropped by 80%. What previously took hours now took minutes.

• Accuracy improved significantly. The AI’s vetting decisions aligned closely with those of our most experienced human reviewers.

• The recruitment team gained bandwidth. Instead of being bogged down with initial vetting, they could focus on more strategic tasks—like engaging with clients and providing personalized support to top-tier talent.

The AI agent became an invaluable member of our team. It could analyze profiles at scale, flag potential red flags, and highlight exceptional candidates based on our frameworks.

But beyond the operational benefits, the AI agent had a deeper impact. It reaffirmed our commitment to innovation and efficiency. It allowed us to maintain our promise to clients—to deliver vetted, high-quality talent from Africa—without compromising on speed or quality.

Lessons Learned

Building and deploying an AI agent wasn’t without its challenges. Here are some key lessons we learned along the way:

1. Data Quality Matters: The accuracy of any AI model is only as good as the data it’s trained on. Starting with clean, standardized data is essential.

2. Human + AI = Best Results: AI can handle the heavy lifting, but human oversight is still crucial. Our recruitment team provides context and judgment that the AI can’t replicate.

3. Continuous Improvement: Our Talent Frameworks are living documents. As the industry evolves, so do our standards. We continuously update the AI model to reflect these changes.

The Future of Talent Vetting at ProDevs

Deploying the AI agent was a game-changer for ProDevs. But we’re not stopping there.

We’re already exploring ways to make the AI agent even smarter. For example, we’re looking at ways to incorporate feedback from clients and candidates to further refine the vetting process. We’re also exploring how AI can help with other parts of the recruitment journey—from matching candidates to roles to providing personalized career advice.

Our goal is simple: to continue connecting African tech talent with global opportunities, faster and more efficiently than ever before.

An Inspirational Journey

At ProDevs, we often talk about creating opportunities. But this experience reminded us that opportunity isn’t just about opening doors for others—it’s about embracing change and innovation within ourselves.

Deploying the AI agent wasn’t just about solving a bottleneck. It was about reaffirming our commitment to our mission. It was about finding new ways to deliver on our promise to talent and clients alike.

Today, as we continue to grow, we do so with the confidence that we’re building something sustainable. Something impactful. Something that scales.

And that’s a journey we’re proud to be on.