_________ __ __ ____ _____ ___ __ / ____/ | / / / / / __ \/ ___// | / / / / / /| | / / / / / / / /\__ \/ /| | / / / /___/ ___ |/ /___/ /___/ /_/ /___/ / ___ |/ /___ \____/_/ |_/_____/_____/\____//____/_/ |_/_____/
AGENTS DON'T WANT OUR WORDS
// WHAT IT DOES
Agents in a pipeline burn most of their tokens and time talking to each other; Anthropic measures a single agent at about 4x the tokens of a chat, and a multi-agent system at 15x. CALLOSAL plugs into a local multi-agent system, regardless of the models, and cuts that cost: no decoding in agent-to-agent communication, so fewer output tokens, a faster end-to-end run, and accuracy that holds or improves.
// THE NUMBERS
Our benchmark: one four-agent pipeline (plan, solve, check, decide), one open-weights model, seven public task sets, identical prompts and token budgets in both runs. PLAIN TEXT is the pipeline as every stack runs today, agents decoding words at each other. CALLOSAL is the same pipeline with our product plugged in; nothing else changes. Any agents, any roles: the product does not care what they do.
| BENCHMARK | PLAIN TEXT | CALLOSAL | Δ ACC | TOKENS | SPEED |
|---|
Internal runs, August 2026: one four-agent pipeline, one open-weights model, seven task sets, same prompts and budgets in both arms; only CALLOSAL differs. Raw runs on request.
// WHAT WE PROVIDE
Same CALLOSAL, same numbers above. Pick where the agents talk: inside your building, or on our GPUs behind one API. Both plug into your pipeline without touching the agents or their prompts.
CALLOSAL installed on your own hardware. Your GPUs, your models, your network; nothing leaves the building, ever, and it runs offline once installed.
CALLOSAL as a service. You send the input and the specs, we run the agents on our GPUs, you get the output back. No install, no hardware, live in an afternoon.