Gather all the context, let agents do the work, and a company can be built differently: how it is made, and how its people are paid.
Our founder has built a company before, the old way. This one starts from the context.
One person runs twenty agents in parallel. Each brings the whole context of a decision. They decide, and take the next one.
Once contribution can be attributed, pay can follow it. Like a salesperson’s commission, for everyone who moves the company forward.
Models got cheap and tools got easy. The one thing agents still miss is the context people share out loud: in meetings, on calls, in rooms, at someone’s desk.
We use agents all day, and they live on the screen. When the work moves to a meeting room or a phone call, they lose the thread.
We can be the bridge from the digital world into the physical world, for agents.
A shared memory of what it knows, for its people and its agents. Speech is its most important source, and its hardest.
Everyone is racing to build agents and brains. We build the one thing all of them need and none of them wants to build: capturing what people say at work, and making it safe to use.
A product form factor for the agentic era. Compose it as you like.
Headless in your product, raw through the API, into your agents over MCP, or a whole app under your name.
Three ideas and one listener, all on one tree. Say it “afer”.
The mark that starts a word in a model’s tokens. Up in the crown, what was said reaches agents as tokens.
The old letter ash. In Norse myth an ash tree, Yggdrasil, holds the worlds together: its crown in the bits, its roots in the atoms.
Afferent nerves carry signals from the senses to the brain. Down in the roots, what people say is carried in.
Yggy is _æfer’s ears. It listens only where your company and each person allow it. Meet Yggy →
_æfer comes out of HappyScribe and is backed by it. HappyScribe was there in 2017, when speech-to-text became good enough to use. Since then linguists have checked what the machines heard, and those checks trained the models.
Speech to text, every speaker separated, many languages, and people in the loop checking the result.
The same listening in meetings, calls and rooms, with 130+ languages and 10+ speech engines, ready for the agents you build.
Infrastructure for context, where agents meet the physical world. Ship in 5 minutes.