At Frontier, speed and precision are key to smarter textile sourcing. We add new features to TextileCloud, from prompt based search to instant tariff insights, and enhance our AI to help brands and suppliers work more efficiently. But even small updates can disrupt critical workflows.

Historically, our R&D and sourcing teams spent hours each week manually checking search results, tariff calculations, and brief generation outputs before each release. In 2020, we developed an AI powered testing framework that is easy for anyone to use, requires no coding expertise, and adapts to constant platform changes.

New Frontiers in AI Powered QA and Workflow Automation

Our AI automation works in natural language, meaning a team member can simply type something like “Search for recycled polyester fabrics under 150 gsm and check the top 10 results” or find fabric via image search, and the tool will execute that workflow across our systems in real time.

Within hours of setup, we had automated regression tests for:

• Material metadata accuracy

• Filter and category performance

• End to end brief generation from supplier data

• Sustainability estimator

• Downloadable 3D files for digital product creation
  

From Idea to Innovation in Minutes, Not Weeks

Selecting fabrics for product sampling once required lengthy processes, multiple emails, physical swatches, and hours of repetitive work. Now, our AI gathers requirements, interprets design needs, and instantly delivers matching fabrics with full specifications. This has cut the concept to a prototype timeline, reduced physical sampling, and lowered related costs by up to 30 percent%.

Users can also generate and download Excel or PDF reports from the dashboard with the latest fabric data, including 3D assets, collections, material content, and sustainability metrics, providing up to date insights without manual effort.

Challenges We Have Tackled

Like any general LLM based system, interpretation can be unpredictable, sometimes too rigid and sometimes too creative. To address this, we have built guardrails that fall back to direct API checks for deterministic tasks, flag potential data anomalies for human review, and handle complex textile queries with specialized prompt templates. Advanced cases, such as verifying search accuracy across multiple languages or testing highly nuanced fabric classifications, are still evolving, but our AI capabilities continue to grow with each iteration.

Tangible Results for Our Users

The same AI principles are now integrated into TextileCloud features our customers use daily:

• 30% faster sample development

• 25% lower physical sample costs

• 100% complete digital fabric database

These gains mean brands and suppliers can move from idea to production with fewer bottlenecks, less waste, and more certainty.

Conclusion

Our AI framework has reduced hours of work to minutes without sacrificing accuracy. It is transforming sourcing, boosting collaboration, and enabling data driven decisions.

If you want to see how our AI is transforming textile sourcing, contact us.