Data Methodology
Hokai is built on accurate, honest tool information. Our founder has over a decade of experience in regulated industries — fintech, banking, and compliance — across Europe and Southeast Asia. That background informs our commitment to data integrity. We built Hokai because we were frustrated with affiliate-driven directories where whoever pays the most gets the top spot. Our methodology is designed to resist that.
How Tools Are Discovered and Added
Tools enter the directory through multiple channels: team research, user suggestions, and monitoring of the AI tool landscape. We evaluate each tool for fit and quality before adding. We do not add tools in exchange for payment. Suggestions are welcome — email info@hokai.io with tool name, URL, and a brief description.
What Data We Collect Per Tool
For each tool we collect: name, vendor, description, pricing (min, max, notes, free tier), key features, pros and cons, target audience, platforms (web, desktop, mobile), architecture, capabilities, compliance certifications, and integration information. We also store technical audit data where available — API robustness, latency, and similar factors — to support health scores and recommendations.
How Data Is Kept Current
We use automated scanning to monitor the internet and keep tool information current. Our systems run regularly to verify pricing, features, and links. Manual review supplements automation. User reports of outdated information help us catch issues faster — email info@hokai.io if you spot errors.
Quality Assurance
We verify accuracy through multiple layers: automated checks, manual review, and user feedback. Tool profiles show the good and the bad — we do not whitewash. Our rankings and leaderboards are based on real signals: download numbers, team usage, and community trends. We do not accept payment to rank tools higher.