Steps, not a prompt
Read, check, write: each step does one thing. That is what lets you put a fast model on sorting and a strong one on analysis.
An invoice comes in, it comes back captured. A CV comes in, it comes back as a sheet. You drop it, the agent does the work, and you see what it read and what it cost.

Read, check, write: each step does one thing. That is what lets you put a fast model on sorting and a strong one on analysis.
We change the task without breaking the one already running. The new version only goes to work once it is published for your space.
What went in, what came out, the state of each step, the model called and its price. You reopen it, you run it again.
You do not build the task yourself. That is deliberate: getting it right takes several passes on your real documents.
To an agent in the messenger, or on a call. One sentence is enough to start.
Our team splits the task into steps, picks the model for each one and connects your tools. Then we install it in your space.
By dropping a file, by writing to an agent, at a set time, or from your own software.
On a video call: we go through the tasks eating your team's time and pick the best one to hand to AI.
We connect ERHA to your real repository. You judge on what goes live, not on promises.
Your space goes live: every job is tracked, its cost shown and capped.
One conversation is enough to scope it. After that it depends on the number of steps and how long it takes to get access to your tools. You test on your real files before it goes to work.
The job stops where it got to. You open the detail, see the step that failed and what it had read, and run that one again without redoing the rest.
Yes, and without six months' notice. The model changes step by step, and the task keeps running the same way.
We'll show you ERHA on one of your own files, in 30 minutes.