About Us

Your AI agent needs tractable context.

AI isn't the future anymore — it's already changing our present. But here's the kicker — only 26% are actually usable.

Any functional agent will have three parts to it:

• The models
• The workflows
• The context

The first two are already being solved: Models are crushing SoTA records every day, while workflows are more or less direct ports of real-world repetitive processes, specifically tailored to businesses. That's the UX that MCPs strive to solve for.

The real problem lies in the context.

Context engineering is the next frontier for AI adoption.

As LLM context windows 10× over every year (a trend that's holding pretty well so far), data explodes at 100× more. So here's the uncomfortable truth:

Data is always going to exceed LLM context window sizes, no matter what.

Thus, the question for any AI-enabled business is not IF they would need a new context layer and context engineering in general, but WHEN. Turns out, that's pretty soon. Beyond ~10 sessions per user, businesses need to treat memory and user-specific context as mandatory requirements for their users. And that's the average number of chat sessions that a customer has with an AI chatbot in a month.

“95% of generative AI efforts will fail by 2026–27.” — MIT

And the reason is lack of proper contextualization.

So, you don't just need context — you need tractable context that you can verify.

That's the sole purpose of us building Alchemyst AI.

The world will be moving towards Agent Era 2.0 — where context matters more than prompts. Prompts can be auto-optimized, thanks to accurate context storage and retrieval.

This is the vision we bet our entire company on, a year ago. With this coming true, we want to say one thing:

“Everyone will upgrade — and the ones using Alchemyst AI will be at the forefront.”

~ Signing off,
Anuran and Uttaran