Our story

Hi, we're
Sorvian.

We got tired of watching teams choose between useful AI and safe data. So we built the layer that lets you have both.

Enterprise AI shouldn't ask you to pick between the answers you need and the data you protect.

S

— The Sorvian team

How we got here

The tools kept getting smarter.
The rules kept getting harder.

Sorvian started from a question we kept hearing from security, engineering, and legal teams at the same company: “Can we actually use this AI without ending up on the front page?”

The answer was usually some version of “not really.” Teams either sent everything to a public model and crossed their fingers, or redacted so much that the model came back with confident, useless answers.

We thought the tradeoff was avoidable. A small group of us started sketching what a middleware layer would look like — something that could understand a company's data as deeply as a frontier model, but without the data ever leaving the company's walls. That sketch became the distillation pipeline.

A few years later, that's still what we're building. A bit bigger, a lot more polished, and still pointed at the same problem: keeping the answers without giving up the data.

The team

Builders, researchers, operators.

We wanted to work on the problem every AI team is going to run into — and we wanted to be the answer when they did.

Our mission

Make enterprise AI safe enough to actually use.

Every company has knowledge worth using with AI and data worth protecting. We're building the middleware that lets both things be true at the same time — without the tradeoff nobody should have to make.

What we believe

Three things we keep coming back to.

Security shouldn't slow you down.

If the safe path is also the slow path, teams will find another path. The job is to make the secure option the obvious one.

Clever beats complicated.

We'd rather ship one simple capability that everybody uses than five clever ones nobody trusts. The pipeline stays small on purpose.

Our customers' data belongs to them.

Not to us, not to a frontier model, not to the ambiguous space in between. That's a posture, not a feature.

The people

A small team
with a specific obsession.

We're remote-first across North America and Europe, with a handful of regular in-person gatherings. Here's roughly how the team breaks down.

JH
AR
MK
TP
NS
LQ
DV
RB
EK
+ more
Who we hire

The Engineers

Backend, platform, and data folks who obsess over reliable systems and tidy abstractions.

Who we hire

The Researchers

Applied ML, NLP, and retrieval people — the ones pushing what the pipeline can understand.

Who we hire

The Operators

Solutions architects, customer engineers, and consultants who make rollouts feel easy.

Who we hire

The Designers

Product and brand folks who keep the software from looking like the boxy enterprise software they remember.