Invisible for Consumer | Invisible Technologies

Merchants guess. Systems know.

Consumer businesses sit on gold and act broke. Data everywhere, insight nowhere. Most decisions are still made by instinct and PowerPoint.

AI can see what sells, where, and why. But it only works if you trust the math over the mood.

Certified and compliant.

Our commitment to enterprise-grade security is one reason nearly every major foundation model has relied on Invisible to accelerate the development of their AI applications.

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Use cases

See how leading firms are streamlining operations and scaling insight.

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ML demand forecasting

Forecast demand for inventory, labor, and pricing while using trend analysis to optimize product planning and store design.

Supply chain optimization

Streamline vendor management and enable zero-touch ordering with real-time communication, automated documentation, and rapid “what-if” supply chain analysis.

Personalized promotions

AI identifies the optimal offer for each customer segment, increasing conversion and retention.

Operations efficiency

Optimize operations with decision intelligence for AI-driven site selection, fraud detection, inventory tracking, and computer vision.

Customer engagement optimization

Improve customer experience with AI-powered chat, automated CSAT tracking, chargeback audits, and personalized post-purchase follow-up.

Financial analytics & automation

Automate AP/AR, analyze budget variances, and accelerate month-end close to improve financial accuracy and decision-making.

Our approach

We embed with your team, observe how work flows, and build systems that align with what’s already in motion.

Trusted by

Invisible helped Nasdaq streamline a data integration process, reducing customer onboarding time and saving 10,000 developer hours.

Invisible improved Cohere’s data quality and scalability, enhancing multilingual, coding, and reasoning capabilities to strengthen its enterprise-ready AI performance.

Invisible automated processes like invoice reconciliation, W9 processing, claim approval letters, and compliance support, resulting in significant cost and time savings.

Invisible's team worked within the client's platform to review model conversations from the research team and assess the level of accuracy of the model responses.

Invisible's team stepped in to review partially completed conversations between different models. We analyzed the search results, reference material, and model responses.

Consumer