Kraken at the Core of Content and User Experience

Medical Tourism Review is an information-driven platform. For us, the quality, usefulness, and variety of content matter most.

Over the years we explored many approaches, and Kraken proved the most effective. It lets us deliver high-quality, diverse information while avoiding heavy manual labor, complex data handling, or maintenance. Content checks remain quick and easy for our team.

The Stakes: Why Content Quality Matters in Medical Tourism

When a visitor arrives searching for treatment options, they expect accurate, up-to-date, and varied details: which clinics offer which procedures, approximate costs, reliable contact information, and correct addresses. Meeting that expectation is a top user-experience goal.

We also aim to serve as many people worldwide as possible. Today we cover 100+ countries and list more than 5,000 clinics. Ensuring this vast content is searchable, accurate, rich, and easy to read often felt overwhelming - yet we refused to compromise.

Many experts told us the task was impossible. We persisted, not because we were sure we could do it, but because we knew it had to be done.

Early Attempts & Roadblocks

Traditional manual workflows never reached the quality or breadth we wanted. It involved a huge team of technical content writers, many managers, developers, and ultimately bloated budgets to massive sizes and consumed 99% of management’s time. To solve this complex problem we had to rethink the challenge technically: What can we automate to raise content quality without thousands of hours of human effort?

Pivoting the Lens: Automate or Bust

And automate we did. We broke the workflow down step-by-step - by domain and function - and automated every stage we could. Inevitably, some automated outputs still needed content checks, and in places the results fell short of our UX standards.

Past experiments with machine-generated submissions missed the mark - captions were dry, technical, or hard to read.

Enter Kraken: Architecture & Workflow

When we began working with OpenAI GPT on other products, we saw a way to achieve both the quality and scale we needed.

We redesigned many automations so AI could take over tasks where rule-based systems fell short - everything from wording generation to data validation. Steps that once required human oversight are now handled by the model.

The result is a multifaceted, multi-step system that delivers the breadth and quality we envisioned - at a fraction of the cost of any manual alternative.

Kraken now pulls data from multiple sources, cross-verifies it for freshness, and, where helpful, uses advanced AI to generate reader-friendly descriptions packed with the context users need. Prompt engineering took time: we iterated until the tone, depth, and structure matched our UX standards.

Quality Assurance at Scale

In early phases we reviewed every entry to fix errors and raise the bar. Today we spot-check random batches to ensure the system still performs and hallucinations remain near zero.

Results That Moved the Needle

The payoff is huge. Our content team is freed from tedious data collection and entry; they focus on strategy - identifying gaps, updating key information, and pursuing creative ideas that lift the entire platform.

Lessons for Builders

I believe we should never abandon ambitious goals simply because they seem out of reach. Some problems are too important to leave unsolved. A team with high standards and clear purpose can achieve results once thought impossible.

This experience reinforced three lessons:

1. Aim high - big challenges spark the creativity needed to solve them.

2. Hold the quality line - only meaningful standards keep a team motivated long-term.

3. Trust your people - push for excellence, reject half-measures, and watch them work magic.

Never say never. If a solution matters, keep probing until you find it.

Reard more about Kraken on HumanFace Tech >>>