- Adnan Shahid

Why build a education and job search space?

After searching for a job twice throughout my career and observing friends in their job hunts, I have come to realize that the hiring process is broken at several stages. There’s a clear UX and outcome gap. I am personally determined to address this issue.

(jobs may not exist in the future 😂)

While jobs may evolve or disappear over time, the fundamental human need to contribute value through work remains constant.
Just as society evolved from bartering to currency to optimize value exchange, our platform will create the next evolution of work, moving beyond traditional jobs to seamlessly connect skills with flexible opportunities.

Solving a Core Economic Problem: Unlocks immense value for individuals and economies alike.

Perfect Timing for Innovation: Capitalizing on the global shift from degrees to a skills-first world through building Education and job search space.

AI for Hyper-Personalization: Leveraging AI to deliver tailored learning and career navigation at scale, a key differentiator.

Massive Market Opportunity: Tapping into a combined $450B+ global EdTech and HR Tech market, with every student representing a lifelong career monetization potential.

Diverse Revenue Streams: B2C subscriptions/premium features, B2B SaaS for hiring, and institutional partnerships for placement and up skilling.

High Retention & LTV: Long-term user engagement across career journeys, enabling 3-10 years of monetization per user.

Powerful Network Effects: Growing learner and recruiter bases create a defensible two-sided marketplace with superior data insights.

AI-Driven Differentiation: Opportunity to dominate the "copilot for careers" space with personalized, conversational, and guided AI experiences, unlike legacy players.

Job description

No clear information on

interview processes, timelines,

required skill sets, and compensation

Application and shortlisting

Over-reliance on templates and keyword-driven screening often overlooks talented candidates, leading to exploitation of the system and shortlisting errors.

Lengthy, complex, ineffective AI skills matching application process.

Platforms lack the flexibility to adapt to diverse recruiting processes and workflows used by different recruiters.

Interview/Interaction

Feedback

Platforms fail to capture unstructured data from recruiter-applicant interactions, leaving candidates without feedback and recruiters burdened with manual documentation.

Efforts to improve hiring through candidate feedback often fail due to survey fatigue, vague questions, and low response rates, resulting in poor insights and minimal impact.

Applicants are often left without feedback or responses, leaving them feeling ignored, unworthy, and without insights to improve or understand their performance.

Problems at different stages:

While applicants seek clear and timely communication, recruiters face manual tasks and rigid platforms, leading to a broken and inefficient recruitment experience.

Job description

Encourage recruiters to provide clear information, and recommend courses from our educational platform to engage and helps in preparing applicants for the interview in waiting time through seamless UX .

AI bot to provide information based on past recruiting data, success metrics, company culture of specific company to provide clear information reducing ambuiguity.

Application and shortlisting

Developing an AI shortlisting engine that holistically evaluates candidates through AI video assessments, semantic analysis of resumes, and deep dives into projects (portfolios, LeetCode, GitHub), intelligently identifying transferable skills and hidden potential to ensure no talent is overlooked.
Recommend courses from our platform in case of skills gap for the desired role.

Provide recruiters with a flexible system to customize hiring pipelines, assessments, and communication, tailored to any company size and strategy, with built-in learning and feedback tools.

Interview/Interaction

Feedback

Real-time AI-powered interview analysis: Utilizes AI to process unstructured interview data in real-time, providing objective performance evaluations and capturing key job-specific metrics for every applicant, reducing recruiters manual work.

Replace long surveys with short, contextual micro-feedback at key touch points, motivating applicants to respond by offering access to their interview performance insights.

Use AI-powered interview analysis insights to auto-generate constructive post-interview feedback, highlighting strengths and improvement areas, and link it to learning modules to support applicant growth.

Potential Solutions at different stages:

Problem:

Over-reliance on templates and keyword-driven screening overlooks talented candidates and leads to shortlisting errors. Traditional AI-based matching is often lengthy, superficial, and ineffective at recognizing real skills.

AI Prototype: Smart Talent Shortlisting Engine

Solution:
Built an AI-powered shortlisting engine that holistically evaluates candidates using:

AI video assessments for communication, intent, skills and expectations.

Semantic resume analysis using LLMs

Deep skill validation via project portfolios, GitHub, LeetCode and others.

Transferable skills mapping to uncover hidden potential

This system ensures a more inclusive, accurate, and efficient candidate evaluation, beyond just buzzwords and pedigree.

What do you think needs to change about how people upskill?

Fostering a culture where continuous learning is expected, encouraged, and built into career progression.​

AI-driven platforms that assess individual skill gaps, analyze career aspirations, and recommend dynamic, tailored learning modules. This means personalized content delivery, adaptive pacing, and varied formats (micro-learning, simulations, projects) based on individual needs.

Up skilling should focus on practical, project-based learning and verifiable skill credentials, not just course completions, ensuring alignment with in-demand, real-world competencies.

Platforms should seamlessly link learning to job opportunities by recommending courses based on market demand and updating profiles to show clear pathways to specific roles.

AI-powered feedback mechanisms that analyze performance in learning modules, simulations, and even interview practice. This feedback should be actionable, highlighting areas for improvement and suggesting specific resources, creating a continuous loop of learning and refinement

Thank you.