The Alchemyst AI Blog
Journaling how we make Alchemyst AI the best and most trusted context layer in the world.
Your NPS Survey Has a 12% Response Rate. Voice Fixes That.
Email surveys get a number. Voice AI gets the reason behind the number — at 35.2% response rates and ₹10.79 per response.
You Spent ₹3 Lakh on Voice AI and Got 200 Leads. Where Did the Money Go?
A forensic breakdown of why most voice AI budgets underperform — and how context engineering changes the math.
Your Voice AI ROI Is Negative Because Your Agent Has Amnesia
When your AI agent starts every call from zero, it wastes time re-establishing context. That overhead makes your unit economics collapse.
Why Your Voice AI Connection Rates Are Stuck at 15%
Most outbound voice AI campaigns in India connect on 8-15% of dials. The root cause isn't your lead list — it's your agent's missing memory.
Why Your Retargeting Campaigns Perform the Same as Cold Outreach
If your voice AI agent doesn't use what it learned from the first call, retargeting is just cold calling with a smaller list.
Voice AI for NPS vs. Email vs. SMS: When to Use What
A neutral comparison of NPS collection channels — response rates, cost per response, qualitative depth, and when each makes sense.
Voice AI Pricing in India Doesn't Tell You What You'll Actually Pay
Per minute, per credit, per outcome — none of these pricing models capture the metric that matters: cost per qualified outcome.
Two EdTech Deployments, 45,000 Calls, One Pattern
JK Shah Classes and Unacademy ran different use cases at different price points. The context layer delivered consistent results across both.
Your Feedback Loop Is 3 Weeks Long. Here's How to Close It in 3 Days.
Voice AI compresses the NPS collection cycle from weeks to days — because feedback is perishable and speed determines actionability.
You Don't Need the "Best" Voice AI. You Need the Right Context Layer.
A 300ms voice agent with good context outperforms a 100ms agent with none — because the fast agent says the wrong thing quickly.
Multilingual AI Voice OS for High Volume Customer Interactions
Discover why stateless AI fails global enterprises and how context engineering solves the multilingual challenge. Explore how the Kathan engine transforms high-volume customer interactions with advanced state management.
Alchemyst at 2026 - the year ahead
2025 was a huge year for us - for both product and our mission. The world finally "got" why AI needs context and memory, and finally people woke up from the dream that AGI will be achieved with compute. Here's what we did for 2025 - and how we're looking at 2026.