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Overview
TRUSS is a fast-growing B2B technology company at the forefront of retail AI in fashion. Operating across Europe and the U.S., TRUSS empowers luxury resale platforms to thrive in the era of circular fashion by transforming unstructured fashion data into intelligent, searchable, and insightful databases. Their core focus: organising fashion data at scale through intelligent cataloguing, style analysis, and metadata enrichment.
Challenge
As TRUSS expanded, it encountered a critical challenge: scaling data annotation operations without compromising quality or domain specificity. Success hinged on producing high-quality datasets enriched with deep fashion knowledge – something essential for training AI models in a space where style labels like “Grunge,” “Military,” or “Football Hooligan” are highly subjective and culturally nuanced.To meet the demands of luxury resale platforms and internal teams alike, TRUSS needed a strategic annotation partner who could:
- Deliver consistent results at scale
- Navigate the ambiguity of fashion taxonomy with cultural and contextual fluency
- Manage multiple simultaneous projects under tight deadlines
- Maintain operational excellence while meeting evolving client expectations
Overcoming these challenges was essential for TRUSS to deliver high-quality, reliable data that would support business growth, satisfy industry standards, and strengthen their position as a leader in fashion data intelligence.
Solution
TRUSS partnered with Aya Data to build a robust, scalable solution for fashion-specific data annotation. What began as a focused footwear project quickly expanded into a strategic collaboration, as we demonstrated our ability to combine fashion fluency with annotation precision.
Technical Challenges Solved
The core technical hurdle was ensuring consistent, culturally aware annotation of nuanced fashion styles. With attributes like “Grunge” or “Football Hooligan” requiring deep contextual understanding, it was critical to avoid annotation drift across large datasets.
We addressed this challenge by:
- Designing a custom training program based on TRUSS’s proprietary taxonomy
- Building annotation workflows capable of handling subjective, high-variance style categories
- Embedding continuous feedback loops to reduce inconsistencies and improve ML-readiness for use cases like GOAT’s style analytics
This elevated TRUSS’s capabilities from basic object tagging to enriched metadata classification, which is essential for machine learning, retail AI, and advanced fashion analytics.
Operational Challenges Solved
As TRUSS scaled across new categories and client demands, operational efficiency became just as critical as technical accuracy.
The Aya Data team helped solve these through:
- Rapid annotator onboarding to meet shifting scope and fast-paced timelines
- Workflow adaptability to accommodate evolving briefs and client deliverables
- Reliable throughput without sacrificing quality – key for supporting internal teams and external platform partners
Together, these solutions allowed TRUSS to scale annotation operations confidently – fueling innovation in resale fashion and reinforcing its leadership in fashion data intelligence.
Results & Impact
Our collaboration with TRUSS produced measurable, business-critical results. By outsourcing complex fashion data annotation to a specialist partner, TRUSS was able to elevate both the speed and sophistication of its data pipeline.
Key Outcomes
- Annotation accuracy rose above 92%, especially for culturally nuanced tags like “Grunge” and “Football Hooligan”
- Throughput of annotated images tripled without sacrificing precision
- Internal QA workload was significantly reduced, allowing TRUSS to reallocate team resources to strategic R&D
- More robust AI training datasets now power TRUSS’s predictive models and trend analysis capabilities
Long-Term Value
he impact extended far beyond short-term metrics. With a scalable annotation infrastructure in place, TRUSS is now positioned to:
- Expand its SKU-level catalogue and refine advanced style taxonomies
- Launch real-time product insights via an upcoming API
- Deepen collaboration with luxury resale fashion and retail partners
- Drive innovation forward in fashion analytics and retail AI
Beyond productivity gains, the partnership also set a new internal benchmark for quality and cross-functional coordination, laying the foundation for TRUSS to lead in data-driven fashion intelligence.
A Word From TRUSS: Delivering on Core Commitments
At a critical stage of our growth, we needed more than just annotation accuracy—we needed a partner who could adapt with us, communicate transparently, and keep quality front and center. Aya Data delivered on all three.
- Exceptional Customer Experience: Throughout our partnership, Aya Data consistently demonstrated a deep commitment to our success. Weekly check-ins weren’t just updates, they were working sessions that drove real alignment and allowed us to solve problems quickly. Their team was proactive, insightful, and often contributed ideas that improved how we structured and tagged fashion data.
- Agile Project Management: When our project needs shifted or timelines tightened, Aya responded with agility. Their team scaled operations seamlessly and balanced competing priorities without sacrificing quality or clarity. We felt confident handing over complex, style-specific annotation tasks because they consistently executed with precision.
- Uncompromising Quality: Most important was their unwavering focus on quality. Over time, we saw measurable improvements in accuracy and consistency – an outcome that speaks to Aya Data’s iterative approach and attention to detail. The result: datasets we could trust, and machine learning models that performed stronger because of them.
Aya Data wasn’t just a vendor – they became an extension of our internal team.
Conclusion
The partnership between TRUSS and Aya Data demonstrates how the right annotation partner can drive both operational excellence and long-term innovation. By combining fashion expertise with scalable, high-precision workflows, Aya Data enabled TRUSS to transform its data pipeline – powering smarter machine learning, accelerating go-to-market capabilities, and strengthening its leadership in fashion analytics and resale fashion.
With a solid foundation in place, TRUSS is now poised to expand its influence across retail AI, launch API-driven insights, and continue pushing the boundaries of data-driven decision-making in fashion. At Aya Data, we are proud to be a key enabler in that journey, delivering both the precision and adaptability needed in an ever-evolving industry.
To discover how our expert data annotation services can drive similar results for your business, contact us today or request a free pilot.
Disclaimer: Aya Data respects client confidentiality and will not share client details or project information without the client's approval.
