The Kryotta blog
Guides and comparisons on working with every AI model — Claude, Gemini, Llama, Mistral, DeepSeek and more — plus what we're building.
5 myths about Gemini 2.0 and reasoning models that waste your Razorpay dispute budget
Reasoning models aren't always better for dispute responses, and Gemini 2.0 doesn't replace your entire stack. Learn which model fits which task to cut costs without sacrificing quality.
I made 52 product shots with Stability AI then Reels with Luma and Nova: which format got ₹18,000 in Flipkart orders
I tested AI-generated static images against AI video Reels for brass home décor on Flipkart. The video listings converted 47 sales (₹17,860) versus 22 sales (₹7,480) for images—more than double the revenue.
I used 4 AI models to write 140 GST invoice dispute emails: which one per query type
I tested Claude, Gemini, Llama, and GPT-OSS on 140 real GST queries from my textile business. Here's which model handled reverse-charge disputes, GSTIN errors, and amended returns best—and why it mattered.
I used o1 vs Claude vs Gemini to debug 32 UPI webhook failures: which model per error
I tested o1, Claude, and Gemini on 32 real UPI webhook failures during a Diwali sale. Here's which model solved each error type fastest and cheapest.
5 myths about GPT-4o and Gemini 2.0 that waste your Razorpay dispute budget
Newer AI models aren't always better for handling payment disputes. A jewellery store's real test shows older, faster models like Gemini Flash often win on speed and cost.
5 myths about prompt templates for WhatsApp Business that waste your automation budget
I wasted ₹18,000 on WhatsApp automation chasing myths about template design. One flexible prompt structure cut my manual work from 42% to 11% and dropped costs by 60%.
I used 3 reasoning models to debug 30 Razorpay webhook signature failures: which one per error
I tracked 30 Razorpay webhook signature failures across Claude Sonnet, Gemini Pro, and DeepSeek R1 to see which model caught each error type fastest and cheapest during peak season traffic spikes.
I used AI to answer 6 questions about e-commerce, healthcare and restaurants
I tested AI on real business problems: GST invoice extraction, WhatsApp customer replies, and more. Here's what actually worked and what still needs a human touch.
I used AI in 6 Indian industries for 60 days: what it actually does in e-commerce vs healthcare vs restaurants
I tested AI across six Indian small businesses for two months. Here's what actually worked—and what created more problems than it solved.
5 myths about model per task for debugging that waste your freelance rupee budget
Stop burning rupees on expensive models for every bug. Here's what actually works: route simple syntax errors to Haiku, save Opus for race conditions, and use reasoning models when production fails only under load.
I explained tokens, context windows and hallucinations to my Meesho vendor team — what finally made sense
I tried teaching my vendor team how AI actually works—tokens, context windows, hallucinations—using their own work. Some analogies flopped. Here's what finally clicked.
5 myths about new reasoning models that waste your Razorpay automation budget
Reasoning models aren't always the answer for Razorpay automation. Learn which tasks actually need them—and which ones waste your budget.