See how industry leaders use TaylorType to transform their search experiences and drive business outcomes.
Meridian Commerce, a leading e-commerce platform serving 50M+ monthly shoppers, transformed their product discovery experience with TaylorType's semantic search capabilities.
Meridian Commerce had grown rapidly to become one of the largest multi-vendor e-commerce platforms in North America. With over 15 million products across thousands of categories, their legacy search solution was struggling to keep up.
"Our customers were frustrated," explains Marcus Chen, VP of Engineering at Meridian. "They'd search for 'comfortable work shoes' and get irrelevant results because our system could only match exact keywords. We were losing sales every day."
The platform's search had a 23% "zero results" rate, and customer satisfaction scores for product discovery were declining quarter over quarter.
Meridian chose TaylorType for its combination of semantic understanding and enterprise-grade performance. The migration was completed in just six weeks, with TaylorType's team providing dedicated support throughout.
"What impressed us most was TaylorType's ability to understand intent. A search for 'shoes for standing all day' now surfaces orthopedic and comfort-focused products, not just anything with 'standing' in the description."
Key implementations included:
Within three months of launch, Meridian saw transformative improvements across all search metrics. Conversion rates from search increased by 34%, and average order value grew by 28% as users discovered more relevant products.
"TaylorType didn't just improve our search—it changed how customers interact with our platform," says Chen. "The semantic understanding means we're finally helping customers find what they need, even when they don't know exactly what to call it."
DevHub, a developer tools company with 200K+ active developers, used TaylorType to transform their documentation experience and dramatically reduce support burden.
DevHub's developer platform had grown significantly, and with it, their documentation had expanded to over 2,000 pages covering APIs, SDKs, tutorials, and troubleshooting guides. The problem? Developers couldn't find what they needed.
"Our support team was drowning," recalls Sarah Park, Head of Developer Experience at DevHub. "60% of support tickets were questions that were already answered in our docs. Developers just couldn't find the information."
Their existing search was keyword-based and struggled with developer queries like "why is my webhook failing" or "how to handle rate limits."
DevHub implemented TaylorType across their documentation portal, help center, and API reference. The key differentiator was TaylorType's ability to understand technical queries and match them to relevant content.
"TaylorType gets developer language. When someone searches 'auth not working,' it knows to show OAuth troubleshooting, token refresh guides, and error code references—not just pages with 'auth' in the title."
The implementation included:
The impact was immediate. Support ticket volume dropped by 45% within the first month, and developer satisfaction with documentation jumped from 3.2 to 4.8 out of 5.
"We've completely transformed our developer experience," says Park. "Our docs search is now one of the things developers praise most about our platform. TaylorType turned a pain point into a competitive advantage."
TalentBridge, a talent marketplace connecting 2M+ professionals with employers, revolutionized their matching algorithm with TaylorType's AI-powered search.
Remote · $180k-$220k · React, TypeScript
Remote · $160k-$200k · React, Next.js
TalentBridge's talent marketplace was struggling with a fundamental problem: job titles don't mean the same thing across companies. A "Software Engineer" at one company might be equivalent to a "Developer II" at another, and a "Full Stack Developer" could mean anything from React specialist to DevOps generalist.
"Traditional keyword search was failing us," explains James Rodriguez, CTO of TalentBridge. "A candidate searching for 'machine learning engineer' might miss relevant roles titled 'AI Research Scientist' or 'Deep Learning Specialist.' We were leaving matches on the table."
TalentBridge integrated TaylorType to power both their job search and candidate matching systems. The implementation went beyond simple text matching to understand the semantic relationships between skills, roles, and experience levels.
"TaylorType understands that 'Node.js' and 'Express' and 'backend JavaScript' are related concepts. It knows that '5 years experience' and 'senior level' often mean the same thing. That intelligence completely changed our matching quality."
Key features implemented:
The new search system transformed TalentBridge's core value proposition. Time-to-match decreased by 75%, and both candidates and employers reported significantly higher satisfaction with search results.
"We went from being a job board with search to being an intelligent matching platform," says Rodriguez. "TaylorType is the engine behind that transformation. Our matching quality is now a key differentiator in the market."
Join these companies and thousands more building better search with TaylorType.