HireSight

problem

The Problem

Startups hire on intuition, lose on attrition

Startups and SMEs make hiring decisions based on gut feeling, then lose employees within 6 months because of culture mismatches and unclear role expectations. The cost of a bad hire at a 20-person startup is devastating.

• Hiring decisions driven by intuition, not data
• Early attrition (0-6 months) is the #1 cost for startups
• No tools for SMEs — enterprise HR platforms are too complex and expensive
• Culture-fit assessment is subjective and biased

research

The Research

From intuition to insight

I studied how startups actually hire and what predicts early attrition. The pattern: companies that defined 'employee archetypes' (behavioral profiles that succeed in their culture) had 3x lower attrition.

• Identified employee archetypes as the key predictor of retention
• Mapped the hiring workflow: source → screen → interview → offer → onboard
• Found that the screen → interview transition had the highest drop-off and bias

solution

The Product

Data-driven hiring for startups

Structured the product architecture around three pillars: employee archetypes (define who succeeds), attrition prediction (flag risks early), and intelligent workflows (reduce bias in screening).

• Employee archetype engine — define behavioral profiles that succeed
• Attrition prediction model — flag at-risk hires within 30 days
• Intelligent screening workflows — reduce bias with structured evaluation
• Dashboard showing hiring funnel health and retention predictions

impact

The Impact

Helps organizations make smarter hiring decisions, reduce early attrition, and shift from intuition-led to insight-driven talent management.

reflections

Reflections

The hardest part of this project was translating fuzzy 'culture fit' into measurable product features. The employee archetype framework was the breakthrough — it made the subjective objective.

• Culture fit can be measured if you define the right archetypes
• Attrition prediction is more valuable than hiring prediction
• SMEs need simple tools, not enterprise complexity downsized