Reed.ai

Reimagining recruitment with AI

Role: Lead Product Designer

Project type: 0–1 MVP / Web & Mobile App / UX Strategy & Delivery

Sector: Recruitment

Clients/Customers: B2B and B2C

Building a product from zero, shaped by human connection.

Reed.ai is a conversational AI assistant designed to radically accelerate and humanise the recruitment journey. Built from the ground up as a 0–1 MVP, the tool supports seamless interactions via text or voice, assisting both employers and candidates.

Powered by Reed’s dataset of 15 million CVs, it reimagines how roles are defined, talent is matched, and hiring is managed, from first touchpoint to job offer.

Key wins at a glance

30+ user testing sessions

with 20 employers and 10 candidates over 6 months.

50+
user flows

designed across 15 product epics for both B2B and B2C journeys.

26
agile sprints

from discovery to MVP delivery, with continuous iteration.

6 C-suite level
demos

delivered directly to the CEO of Reed.

My role

Leading design from discovery to delivery

As Lead Product Designer, my role spanned discovery, UX strategy, UI design and delivery:

  • Led all user interviews and usability testing.

  • Designed and iterated wireframes, flows, and high fidelity functional prototypes.

  • Ran stakeholder workshops and storytelling sessions to bring the product vision to life.

  • Presented weekly progress and concept demos to the product owner and C-suite stakeholders, including 6 go/no-go reviews with Reed’s CEO.

  • Collaborated across a multi-disciplinary team: project managers, front- and back-end developers, AI architects, analysts, marketing, and CX.

  • Built and maintained a design system from the ground up.

Vision

Beyond automation - true collaboration

Our goal wasn’t just to build a faster recruitment tool. It was to create a collaborative, AI-powered experience that improves the quality of human connections on both sides.

  • For employers: it writes job descriptions, intelligently shortlists candidates, and schedules interviews.

  • For candidates: it builds rich profiles, surfaces relevant roles, and advocates for their fit.

This two-sided experience is built to reduce friction, build trust, and make hiring feel more human.

Discovery

Shaping the vision through early insight

To ground the product vision in real-world problems, we started by speaking with a small group of recruiters and candidates. These initial conversations weren’t about testing flows or features, they were about surfacing pain points.

For employers, it was the overwhelm of application volume and a lack of intelligent filtering, even with existing tools. For candidates, it was the frustration of being ignored, the black hole of unanswered applications, and a lack of visibility or feedback.

These early signals shaped a shared belief: that the recruitment process wasn’t just inefficient, it was impersonal. And that both sides deserved better.

We used these insights to define two core experience goals:

  • Make the process more human and transparent

  • Design for collaboration, not just automation

Solution

Let employers make the first move

The core innovation was flipping the typical recruitment interaction:

  • AI matches candidates to job specs using shared criteria.

  • Candidates are presented anonymously to reduce bias.

  • Employers express interest first and request full profile access.

  • Candidates then choose whether to share their details and engage.

This model reduces noise for employers, empowers candidates, and builds a more respectful, human-centred hiring flow.

Strategy

A two-sided, flexible experience

We structured the product into 15 epics, each focused on a core part of the user journey for either employers or candidates. With both B2B and B2C audiences, this resulted in over 50 distinct user flows.

Our iterative process prioritised quick learning:

  • Wireframes were tested with real users early and often.

  • Flows were refined based on feedback and performance.

  • Patterns were validated through competitive benchmarking.

Accessibility, clarity, and speed were non-negotiable for a product that had to work via both voice and text, at a desk or on-the-go.

Testing & iteration

Designing for real users, not assumptions

Once the vision and core principles were established, we moved into rapid, iterative design, validating each major area of the product with real users.

Over 6 months, we ran 30+ moderated user testing sessions with a wide range of participants:

  • 20 employers (HR managers, Heads of People, recruitment leads, and product owners).

  • 10 candidates (both experienced and first-time users of Reed).

We designed and tested 50+ unique user flows across 15 product epics, ensuring the experience worked intuitively across both B2B and B2C journeys. Every core flow, from role creation and candidate matching, to profile review and interview scheduling, was tested for clarity, usability, and efficiency.

Key to our process:

  • Early-stage wireframes tested for flow comprehension.

  • Competitor-informed structure and interaction patterns.

  • Weekly iterations and refinements based on feedback.

  • Sessions included both desktop and mobile users.

Approach

Micro-feedback, macro impact

We designed for impact at every interaction point:

  • Conversational UI that flexed between voice and text.

  • Micro-interactions that created clarity and emotional feedback.

  • Personalised experiences tailored to each user’s intent.

We also created a user ontology framework to power smarter matching by mapping skills, preferences and role requirements into structured, AI-usable data.

outcome

A new standard for AI in recruitment

After 12+ months and 26 sprints, we launched a first-of-its-kind MVP that rethinks recruitment from the ground up.

Reed.ai blends cutting-edge AI with deep recruitment expertise to create something rare: a product that’s not just efficient, but empathetic. It tackles real problems with practical, human-centred solutions, delivering value for both sides of the hiring process.