PromptEye

Redefining brand monitoring
for the AI era

By optimizing LLM costs by 50% and implementing advanced analytical tools, we built a globally scalable platform that delivers precise insights into brand visibility across major language models.

up to

50%

LLM processing costs reduction

Optimizing brand monitoring efficiency

PromptEye was already providing powerful brand monitoring tools but faced two main challenges:

The need for more efficient data reporting and comparison features.

The need for a more intuitive, user-centric design to make insights easier to access and interpret.

A smarter, more User-Friendly platform

Streamlined data reporting

Enabling users to easily analyze and compare results across multiple timeframes.

Improved usability

With export options and intuitive data visualizations that simplify insight discovery.

Stronger foundations for scaling

Including better monitoring and cleaner project structure.

A foundation for future growth

Ready for further AI-driven personalization and expanded analytics capabilities.

AI-driven cost optimization and enhanced functionality

The project began with our AI Consultant analyzing PromptEye’s challenges and advising on the best strategies for improving performance and usability. Then, our AI Engineer implemented these recommendations, focusing on three main areas: data export, reporting flexibility, and user experience.

Optimizing LLM usage costs

We helped PromptEye implement batch pricing to reduce the platform's LLM processing costs by up to 50%.

This change provided a significant financial advantage for PromptEye, allowing them to scale their operations without compromising performance or quality.

Advanced export options

We implemented an Export Sources feature, allowing users to generate and download prompt data in CSV or Excel format. This made it easier for users to analyze results and share insights across teams.

Dynamic date picker and reporting tools

We customized the date picker component to support single-day or range-based selections (1, 7, or 30 days, with custom options). The reporting logic now automatically calculates metrics such as average position, visibility percentage, and Share of Voice (SOV) — displaying percentage changes between selected periods (e.g., “up 5%,” “down 8%”).

Side-by-side comparison

We introduced a side-by-side view that allows users to compare data from two different dates and visualize differences in brand positioning across models. This made it easier to identify trends and shifts in visibility.

User Experience enhancements

We improved the interface to make navigation and data comparison seamless. Information is now presented more clearly, helping users quickly grasp key insights and act on them.

Project foundations & product improvements

Alongside the core reporting features, we also strengthened the platform foundations and delivered additional product improvements to support smoother scaling and faster iteration.

LLM Audit (LLM-assisted website audit)

We implemented LLM Audit – an LLM-assisted audit that evaluates a website’s readiness for AI-driven discovery. Instead of auditing model outputs, the audit focuses on the website signals LLMs rely on (structured data, crawlability, content hierarchy, authority cues, readability, and writing style).

The feature generates a clear checklist per URL (pass/fail + recommendations) and helps teams quickly identify why certain pages are more likely to be cited or used as sources in AI answers.

Project clean-up and observability

To improve maintainability and speed up investigations when issues occur, we also:

moved the codebase to the PromptEye GitHub organization
added BetterStack for log monitoring and faster error investigation
cleaned up inconsistencies between branches and improved overall project hygiene

UI and product upgrades

We delivered multiple UI and product-level improvements, including:

improved mobile onboarding view
refined email verification flow
prompt suggestions to speed up workflows
added a Spanish (ES) version
updates to plans and packaging

Project audit (on our side)

We also conducted a project audit at our cost, identifying quick wins and longer-term improvements across product, UX, and engineering foundations.

feedback

The client’s opinion

“Working with Vazco helped us make our platform more efficient and user-friendly. Their practical approach and technical support brought noticeable improvements for our customers. We’re looking forward to the future and the possibilities ahead.”

Krzysztof Kościukiewicz

Co-Founder of PromptEye

“Working with Vazco was a game-changer for our AI strategy. They helped us build a solid technical foundation and launch advanced features. Thanks to their deep understanding of the AI landscape, PromptEye is now a faster, more cost-efficient tool, ready to lead the market on a global scale.”

Jakub Borowiec

Co-Founder of PromptEye

The Future: AI-Enhanced Innovation

With these updates, PromptEye is positioned to deliver even more sophisticated brand monitoring solutions.

Our continued partnership will support future developments such as AI-driven content optimization and smarter, more personalized reporting.

Ready to unlock the potential of AI for your company?

Book a free consultation today

Redefining brand monitoringfor the AI era