+ 05 / OUR DIRECTION

Small teams.
Extraordinary possibilities.↗

We believe the most interesting businesses are not always the biggest. They are the ones with a clear direction—and the freedom to follow it.

EV / WORKLOAD-SHAPED INFERENCE
WHY EIGENVECTOR

Keep your direction.
Change your magnitude.

In mathematics, an eigenvector preserves its direction under a transformation, even as its scale changes. Every real workload has directions like that: the prefixes it reuses, the formats it repeats, the way its answers tend to continue.

A generic serving stack treats every request as new. We find those directions and build the inference path along them: a KV backend that remembers what your traffic reuses and a DSpark decoder optimised for how your outputs continue.

We turn powerful models into managed inference APIs: operating the serving stack, optimising it for each workload and keeping server administration with Eigenvector.

THREE PRINCIPLES. ONE DIRECTION.
01 ↗

Independence

Own the application decisions that matter. Choose the supported model, API workflow and inference capacity that fit your business.

02 ↗

Intentionality

Optimise what makes a difference. Start with your real traffic, make trade-offs explicit and measure throughput, latency and cost on the workload your users create.

03 ↗

Possibility

Make ambitious ideas practical. When every GPU does more work, capable inference comes within reach of teams with more imagination than headcount.

A UK COMPANY. AN INDEPENDENT OUTLOOK.

EIGENVECTOR LTD

Registered in England and Wales.
Built for businesses moving forward.

Full company information
COMPANY NUMBER
17434555 ↗
INCORPORATED
2 September 2026
REGISTERED OFFICE
71-75 Shelton Street, Covent Garden
London, WC2H 9JQ, United Kingdom
THE NEXT MOVE IS YOURS

Bring your workload.
We’ll bring the numbers.

Benchmark your workload

One benchmark.
A whole new cost curve.