About — § 00 / Who we are

The lab inside a language intelligence company.

GAI Labs is the research arm of Guildhawk — the company that has spent twenty-five years translating, interpreting, and verifying language for regulated industries. The Lab exists because language is no longer only a translation problem.

Parent
Guildhawk — Est. 2001

Queen’s Award for Enterprise · ISO 27001 · 13,000 customers served

We study how meaning survives translation across machines, humans, and regulators who will be reading the output under oath.

Most translation AI is optimised for fluency on consumer text. We are optimised for defensibility on contracts, clinical documents, and regulatory filings — where a plausible-sounding mistranslation is worse than no translation at all.

We do
Ambiguity detection · Evidence modelling · Human-in-loop verification · Regulated-domain evaluation
We don't
Generic chat LLMs · Consumer translation · Benchmark chasing · Novelty without evidence

Twenty-five years of receipts — from interpreting for government to certifying documents for the Crown.

GAI Labs is not a first-time attempt at language AI. It is a formalisation of research that has been running inside Guildhawk for a decade.

2001

Guildhawk founded as certified translation house for UK government and legal clients.

2012

First internal ML work on terminology consistency across matter-specific corpora.

2019

Queen’s Award for Enterprise (Innovation). ISO 27001 certified.

2023

Akkordia research begins — ambiguity detection for contract language.

2026

GAI Labs formalised. Research agenda published. Papers, code, and specimens in the open.

Four commitments the Lab makes. To itself, to the Guildhawk network, and to the industries who read the output.

These are operating rules, not marketing lines. They govern which projects we accept and which outputs we publish.

P / 01Evidence before narrative.

Every claim we publish is tied to a test set, a method, and a reproduction path. If we cannot run it again, we do not publish it.

P / 02Humans in the loop, on record.

Every output that leaves the Lab has a named human reviewer. No anonymous automation on regulated text.

P / 03Domain over scale.

We prefer a 2B-parameter model trained on legal bilingual corpora over a 400B generalist. Specialisation survives regulatory review.

P / 04Open method, closed customer data.

We publish methods, evaluation harnesses, and specimen analyses. We never publish customer content. Contracts bind the Lab.

Work with the Lab, not with a vendor.

Research partnerships, commissioned evaluations, and regulated-industry pilots:

[email protected]