AI policy builder
Setting up adjudication policies was one of the most complex and time-consuming parts of onboarding with Checkr. Customers had to translate legal requirements into dozens of nuanced rules, and our existing policy builder often took weeks to configure. This created major friction during sales and onboarding and made it hard for customers to feel confident that their decisions were fair, consistent, and compliant.
I led the redesign of this experience end-to-end — understanding why customers struggled, segmenting the needs of SMB, Mid-Market, and Enterprise accounts, and designing a three-tiered strategy that made policy creation dramatically faster, more transparent, and more scalable.
A key foundation of the redesign was Checkr’s existing charge classification model, which uses ML and AI to standardize thousands of charge names into clear categories. I connected this model to a more intuitive, user-facing workflow that helped customers make clearer, more consistent decisions.
The impact was significant: we grew from 16 to 338 customers, increased revenue 2.5x, and helped 7.8 million candidates with records access employment opportunities. The work was recognized by Fast Company’s World Changing Ideas.
Strategic context
The problem: slow, complex, high-stakes policy setup
Customers needed to set up policies that complied with evolving legal requirements, balanced fairness with risk, and worked across dozens of unique roles. But the legacy tool buried critical decisions, lacked context, and offered little guidance — leaving teams stuck in lengthy back-and-forth with onboarding specialists.
Segmentation: SMB, Mid-Market, Enterprise needs differ
Through interviews with 75 customers I conducted, I learned that:
SMB teams wanted simplicity and speed
Mid-Market customers needed a balance of guidance and customization
Enterprise teams required full granular control
This segmentation became a core pillar of our design strategy.
Discovery & Research
What wasn’t working for customers
They didn’t know where to start when building policies from scratch.
Legal complexity made it hard to feel confident in their decisions.
Enterprise teams needed flexibility; SMB teams needed clarity.
Policies weren’t reusable or scalable across roles or locations.
Opportunity areas that shaped our direction
Provide a clear starting point
Build trust and transparency into each recommendation
Tailor complexity to customer type
Dramatically reduce the time-to-value during onboarding
Defining the strategy
Designing a tiered framework that scales across customers
To meet the needs of SMB, Mid-Market, and Enterprise customers, I designed a tiered experience that aligned policy complexity with customer sophistication. This ensured we weren’t overwhelming simpler teams — while still empowering advanced users.
Increasing transparency to improve fairness and trust
The new approach made it easier for customers to understand why certain decisions were recommended — essential for reducing bias and creating more equitable hiring pathways.
Design solution deep-dives
To translate the strategy into an experience that worked across all customer types, I redesigned the policy builder around a guided, confidence-building workflow that adapts to each tier’s level of sophistication.
A guided workflow tailored to each customer tier
Designed a tier-specific approach ensured we didn’t overwhelm smaller teams while still giving advanced customers the power they needed.
Assess Lite (SMB) → guided walk-through, templates, minimal decisions
Assess Standard (Mid-Market) → more control, adjustable rules, self-serve automation
Assess Premium (Enterprise) → full configurability, advanced controls, white-glove support
Assess Lite (SMB): Guided setup, templates, minimal decisions
For teams that needed clarity and speed, I designed a simplified, step-by-step workflow with strong defaults and minimal decisions.
Assess Standard (Mid-market): More control, adjustable rules, self-serve automation
For customers wanting more control, I introduced adjustable rules, editable templates, and a balanced level of automation.
Assess Premium (Enterprise): Full configurability, advanced controls, white-glove support
For sophisticated enterprise teams, I created the most advanced version of the tool with granular controls, customizable automations, and white-glove support.
Design principles
Designing for fairness, clarity, and context
Qualify over disqualify: For fairness ethics, I focused new tiers on labeling records that qualify the candidate instead of disqualifying
More in-context: Championed displaying charge explanations from the policy builder directly on the background check to eliminate the need for customers to need to google statutes
"I like that Assess shows us 'what does this charge mean.' We've spent so much time searching to understand" ~April, Medely
"I love the category explanations and 'What this record means' blurbs" ~Rebecca, Thumbtack
Design system contributions
Built new components and patterns adopted across 3+ product teams
I built modular components that worked across all three customer tiers, enabling faster iteration and future expansion.
Created action card and success card components adopted across 3 product teams
Established progressive disclosure pattern that became standard for complex configuration UIs
Built breadcrumb component with actions reused by onboarding team
