AI provenance & security

Prove what your models wrote.

Security Objectives builds XAMMY, a watermarking and provenance runtime for large language models — built by security researchers who have spent twenty years finding the gaps other teams overlook.

Detector view

The quarterly report shows revenue grew steadily across all regions, driven by strong demand in emerging markets.

SignalStrong
SignedVerifiableJournaled
Illustration: where a semantic watermark concentrates its signal in a sample sentence. The reader sees ordinary text; the detector sees the pattern. Values shown are not detector output.

Why it matters

Your words, provably yours.

Generated text is everywhere and, until now, anonymous. XAMMY gives the people and businesses who produce it a way to keep custody of it — and gives everyone else a way to check. For a writer, that means proving what you wrote and what you didn't. For a business, it means keeping control of what your models put into the world.

Control your IP

Know which text your models produced, and prove it. When your output turns up in a competitor's product, a scraped dataset or a court filing, the claim is verifiable — not a matter of opinion.

Truth in content

Readers, platforms and publishers can check what was written by a machine, even after it has been edited, quoted or paraphrased. Authenticity becomes something you verify, not something you take on trust.

Accountability

Every generated output can carry a signed record of where it came from, and an audit trail that survives editing. When a regulator, a client or a court asks, you have the answer on file.

What we build

Product

XAMMY — LLM watermarking & provenance

Runs on

NVIDIA CUDA (vLLM) · Apple Silicon (MLX)

Status

Working system, pre-release · onboarding design partners

Design partners

We are taking on a small number of design partners in publishing, financial services and legal.

Talk to us — contact@security-objectives.com