Yorph AI Blog: Insights on AI Data Analysis & Analytics Engineering
Insights, updates, and thought leadership on AI data analysis, analytics engineering, and semantic layer best practices.Explore our platform features orlearn about our mission.
How AI Should Handle Attribution and Root Cause Analysis
If you want results you can trust and repeat, "ask a question, get a chart" doesn't cut it.
The workflow that gets you actionable insights needs good assumptions, branching approaches, and validation…
Why Analytics Engineering Needs Better Sandbox Environments
Analytics engineering is messy and iterative by nature - you need to tweak the logic, change the metric definition and try again.
Yet we often run this entire process directly on full datasets.
**Yo…
The Tech Behind Our AI
We've been getting this question a bit lately - "Okay, but what's actually powering your AI system?" So we thought we'd give a quick rundown, minus the architecture diagrams.
ADK Runs Our Agents
We …
Lessons for Agentic AI from the Human Microwork Playbook
By (https://praznat.github.io/)
As a PhD researcher focused on **aggregating annotations**, my work centered on transforming noisy human inputs like translations, syntactic parses, ranked lists, imag…
Security Concerns When Using AI for Data Tasks — and How Yorph Addresses Them
AI tools like ChatGPT, Claude, and others are powerful systems with access to connected tools such as web search, file handling, and code execution. This creates several distinct security concerns:
•…
Lessons Learned Building Reliable Multi-Agent Systems
We are getting ready to launch our agentic data platform and wanted to share what we think are the most important things we've learned. Turns out that building a reliable agentic system is largely abo…
Read on LinkedInThe Product Manager's Data Dilemma: When Great Questions Meet Engineering Bottlenecks
**The Product Manager's Data Dilemma: When Great Questions Meet Engineering Bottlenecks**
As a Product Manager, you have a hypothesis about your product that could unlock millions in revenue. Custome…
Read on LinkedInYou Know What You Need - Now Build It: AI for Analysts
As an analyst, you've been there: you know exactly what data you need, can picture the perfect dashboard in your head, and understand the impact your analysis could have. But there's one problem - the…
Read on LinkedInSecurity at Yorph: What We Keep, What We Don't, and Why That Matters
At Yorph, we know security isn't a checkbox — it's a commitment. When you're working with AI-powered data systems, trust is everything. That's why we're designing Yorph with a security-first mindset, …
Read on LinkedInMulti-Agent Systems: Useful Abstraction or Overkill?
AI agents can do a lot. When you mix a language model with some real-world tools—APIs, scripts, function calls—you get something that can reason, act, and respond in a way that starts to feel useful. …
Read on LinkedInThe Real Key to AI-Driven Data Engineering - It's Not What AI Does, But What It Doesn't Do
In today’s fast-paced, data-driven world, data professionals face an overwhelming set of challenges. Managing vast amounts of data, ensuring scalability and reliability, maintaining security and compl…
Read on LinkedIn