CaaS: Context As a Service for LLMs

“Context Engineering is the delicate art and science of filling the context window with just the correct information for the next step.” — Andrej Karpathy

Sometimes you have access to the correct information, and then the engineering lies in finding the right bytes sequence somewhere in a file stored in the agent environment, in a knowledge graph, or in whatever database. But when your agent needs external information that only private data providers can provide, no amount of engineering will get you there.

One might say that every private data point can be reconstructed from the fragmented public domain, but if it were that simple, companies wouldn’t spend $350 billion on data in 2025.

In addition, your LLM context length is orders of magnitude below the requirement to process public data until it becomes meaningful in an acceptable amount of time. Remember, what your LLM requires is just the correct information for the next step. And when that information is missing, Kirha comes to the rescue.

How it works

Kirha hosts a cluster of MCP servers that expose APIs from private data providers eager to support the agentic revolution. It routes prompts with near-deterministic precision, and when a prompt demands data from multiple providers, Kirha seamlessly composes the required information.

Auth once. Access all partner providers. Only pay for the data you use.