How Handshake cut questionnaire effort by 90% with purpose-built AI they can trust
Executive summary
Handshake is the leading early-talent recruiting platform. 100% of Fortune 100 companies, including Google, EY, Nike, Pfizer, and Hilton, use Handshake to find their next generation of talent. These customers require deep security due diligence, sending customized questionnaires that often reach 100-200 questions covering everything from access controls to AI model governance.
Most of that work fell on one person: Stanley, who leads security compliance at Handshake. It took three months of feeding Wolfia with corrections and authoritative answers. But that investment paid off. Today, Wolfia handles 90% of questionnaire work automatically, and the system keeps getting smarter with each completed assessment.
The challenge
Before Wolfia, Handshake faced several core bottlenecks:
Heavy manual workload: Completing each questionnaire took 2-4 hours of focused work, plus coordination with engineers, privacy counsel, and AI team members for specialized questions.
SLA pressure and slow turnaround: Handshake targeted a 5-day SLA, but some assessments exceeded that. Complex or portal-based questionnaires were particularly difficult to manage.
Rising volume and complexity due to AI: Launching new AI-driven services prompted more nuanced, technical questions. Existing tools couldn't quickly incorporate new information or unstructured content.
Data variety and inconsistency: Questionnaires arrived as spreadsheets, nested tables, PDFs, Word docs, and screenshots. Many contained unusual formatting (checkboxes inside cells, multi-layered tables) that other tools could not reliably parse.
The team needed a solution that could handle messy, inconsistent questionnaires without requiring constant expert input.
Why Handshake chose Wolfia
AI-native, not AI-bolted-on
Handshake needed a platform built from the ground up for AI-assisted security work, not a legacy tool with a thin AI layer.
If you haven't been built as an AI-native platform supporting security and sales teams, you're behind. You can't just bolt on AI and expect it to work for these teams.
Wolfia fit what Handshake needed: answers they could verify and improve over time.
Handles structured and unstructured data effortlessly
Wolfia's ability to parse complex, messy spreadsheets, PDFs and Word docs, screenshots, and unusual formatting was a major differentiator.
This allowed Handshake to process any format enterprise customers sent, without slowing down or requiring manual preprocessing.
Enterprise customers each have their own custom questionnaire. We need to adapt and help them get what they need, and with Wolfia, we can do that.
Corrections stick permanently
When Wolfia got something wrong, Handshake could fix it on the spot. That fix then applied to all future questionnaires automatically. No need to correct the same mistake twice. Response quality improved with every completed assessment.
Results
2-4 hours of work becomes minutes of review
What used to take Stanley 2-4 hours of focused drafting now takes minutes of review. Wolfia generates initial answers in 1-2 hours, and the full process now meets a sub-2-day cycle instead of 5+ days.
90% of answers need no edits
Stanley now reviews instead of drafts. Of the answers Wolfia generates, 90% require no changes. The remaining 10% need minor adjustments for company-specific terminology or recent policy updates. When Wolfia encounters a genuinely new question, it flags it for human input rather than guessing.
Subject matter experts only needed once per topic
Before Wolfia, each questionnaire meant pulling in engineers, privacy counsel, and AI team members, often for the same questions they'd already answered on previous assessments. Now, when a new topic comes up, the relevant expert answers it once. Wolfia learns that answer and reuses it for all future questionnaires.
One person handles the full volume
Stanley manages the entire questionnaire workload without burning out or needing to hire. Enterprise deals no longer stall waiting for security reviews. The security team now focuses on strengthening Handshake's security posture instead of filling out spreadsheets.
Building trust that scales
The three months Handshake invested in training Wolfia built real trust in the system. Stanley now feels confident enough to open Wolfia to other teams within Handshake, knowing the answers will be accurate and the system won't invent information.
The first few months required patience. We had to correct answers, add context, and teach the system our specific language. But now I trust it enough to let other teams use it directly. That's a big shift.
This trust has practical implications:
- Sales teams can check questionnaire status without waiting on security
- Customer success team can answer basic compliance questions independently
- Security team gets time back for proactive security work
Looking ahead
Handshake's story illustrates a pattern: invest in training the AI upfront, and the returns compound. Each correction makes the next questionnaire faster. Each fix prevents the same mistake from recurring. And the percentage of automated work keeps climbing.
For lean security teams facing growing questionnaire volume, this is the path forward: invest in teaching the system, trust that it won't make things up, and watch manual hours turn into minutes of focused review.
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