Resources to build your business with AI.
Articles by Finney Koshy
Where Are We With AI Adoption in 2026 and What’s Next?
Discover the latest on AI adoption in 2026. Learn about the newest trends, benefits, and reasons why AI adoption might stall.
What It Actually Takes to Ship AI in Healthcare
AI note generation looks impressive, but real deployment is a systems challenge. See what it really takes to make clinicians actually use it.
Generative AI in Banking: Use Cases, Risks & Implementation
Learn how generative AI in banking helps cut manual work, improve fraud controls, and upgrade customer experience without losing governance.
LLM vs SLM: Which Language Model Fits Your Needs?
Compare LLM vs SLM to pick the best model for your workflows, data sensitivity, accuracy needs, and budget.
AI Chatbots in Healthcare: Benefits, Risks & Best Practices
AI chatbots in healthcare handle scheduling, intake, and patient questions. Learn what works and how to deploy safely.
7 Examples of AI in Healthcare: Our Digest of What Works in the Industry
This guide shares seven examples of AI in healthcare that speed diagnoses, cut admin, and raise patient safety. See what works now.
![9 Powerful Applications of AI in Finance [Real-World Examples]](https://cdn.sanity.io/images/sr38gnla/production/cb6e1a5bd5adf6cedbf67fa3428f8b730b14a502-1300x681.webp?w=600&fm=webp&q=75)
9 Powerful Applications of AI in Finance [Real-World Examples]
This guide shows 9 real-world applications of AI in finance that cut fraud, speed approvals, tighten compliance, and launch in 90 days.
7 Systems for Real-Time Fraud Detection in the Banking Sector
Learn how these 7 systems for real-time fraud detection in the banking sector help banks fight fraud, meet compliance, and improve customer trust.
Interactive AI: How to Transform Your Business in 2025
See how interactive AI cuts wait times, handles routine tasks, and frees your team to focus on high-value work.
15 AI Stats You Need to Know in 2025
Get the latest AI stats for 2025! Market growth, adoption rates & breakthrough tech trends that'll shape your business strategy.
Building an AI Recommendation System (RAG): 3 Lessons We Learned the Hard Way
We built a RAG-powered recommendation system that matches user preferences against thousands of blog posts. It works great now, but we learned some expensive lessons about rerankers, vector databases, and data structure along the way. Here's what we wish we'd known before we started.
The Reality of RAG
RAG (Retrieval Augmented Generation) combines LLMs with external data sources for enhanced AI responses. While perfect for simple Q&A and chatbots with custom data, our real-world implementation revealed significant limitations with accuracy, debugging, and complex queries that required a more sophisticated multi-layered approach.
AI Model Selection: The Overlooked Secret to Better AI Content Creation
Learn how different AI models perform for content creation based on our real-world testing. Discover the unique strengths and weaknesses of Claude, GPT, DeepSeek, and Gemini for producing marketing content.