aethera

AI where it pays for itself

Language models are excellent at reading messy documents and terrible at being trusted without measurement. We ship the measurement with the feature.

extraction accuracy achieved
97%
extraction accuracy achieved
manual data entry
-89%
manual data entry
evaluated pipelines live
3
evaluated pipelines live

What you get

A scoped use case, not a strategy deck

We pick the one workflow where the volume is high and the errors are visible, and prove it there before touching anything else.

Evaluation before rollout

A labelled reference set and a scored run on every change. If accuracy drops, you know before your customers do.

A human in the loop by design

Extracted fields show their source. Review is one click, correction is one click, and every correction improves the reference set.

Cost you can predict

Token budgets per document type, caching where the input repeats, and a monthly ceiling agreed before launch.

Common questions

To the model provider you approve, under their enterprise terms, or to a model we host for you when the data cannot leave the country. We put this in writing before the first request is made.

It will be, sometimes. That is why nothing ships without a review step and a measured accuracy number for the specific documents you handle.

Usually yes — as a service alongside it rather than a rewrite. The integration point is normally a queue and a review screen.

Related work

Other services

Contact

Tell us what is not working.

A short description of the problem is enough to start. We reply within one working day, and the first conversation is free.