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This 35-page ECHO Report is suitable for technology leaders looking for strategic direction on integrating generative AI into customer support at scale, without compromising service quality or compliance.
The expert: Kirill Markin, Former Head of R&D at SOAX.
The organization: SOAX, a mid-sized global data extraction platform helping businesses gather web data efficiently. The company focuses on scaling automation within data-intensive, user-facing environments.
The problem: SOAX needed to deliver 24/7 customer support while tackling scalability, repetitive queries, and resource strain -- without sacrificing the quality and speed of responses.
The solution: A layered AI customer support system that uses ChatGPT and complementary tools to automate 80% of queries while smartly escalating complex issues to human agents.
Key decisions
Key results
How Geektrust evolved from a manual hiring platform to an AI-powered recruitment solution, driven by real-world hiring challenges.
2. The Problem: The Interview Gap
The hiring bottlenecks faced by both Geektrust and the industry, leading to the need for scalable AI-driven solutions.
3. The Solution: The AI Technical Interviewer Agent
The summary of outcomes and impact of Geektrust’s AI Technical Interviewer Agent solution.
4. Product Evolution: A Closer Look
Geektrust’s product evolution over the years, from manual assessments to ML-driven evaluations to generative AI-powered interviews.
5. Product Development: A Three-Phased Approach
The structured, phased approach Geektrust adopted to build and refine its AI interviewer, ensuring alignment with client needs.
6. Operational Challenges and Solutions
How Geektrust navigated critical challenges, from managing organizational transitions to overcoming market skepticism and adoption barriers.
7. Ongoing Enhancements and Future Plans
Geektrust’s roadmap for expanding its AI-driven hiring platform, transitioning to a SaaS model, and entering global markets.
8. Key Insights from AI Adoption
Strategic takeaways for tech leaders on AI adoption, risk mitigation, and ensuring tangible business outcomes.
9. Conclusion
Final reflections on how Geektrust’s AI adoption model serves as a blueprint for lean startups aiming for scalable, impact-driven AI integration.
References
Citations and sources supporting the key findings and insights presented in the case study.
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