The innovation arm of SignetStack Labs, where the hardest cryptography, agentic AI and the future of the web are invented, and proven before they ship.
SignetStack R&D is the innovation, research and advanced-development arm of SignetStack Labs, where the hardest problems are invented around before they are productised. Its proven output today is the post-quantum, hardware-adaptive cryptographic core that every Signet product inherits, from the Signet Data Trust Network Platform to the independent venture Velocity Quant Technologies. Its frontier reaches into agentic AI, multimodal generation and the future of the web. The method never changes: nothing graduates on a claim, every result is run through the Signet Observatory as a reproducible, tamper-evident proof before it reaches production.
Backend-agnostic post-quantum cryptography: ML-KEM, ML-DSA and SLH-DSA behind a stable interface, so adopting a new NIST-standardized library or algorithm is an additive change, never a re-architecture, and never invalidates historical records.
Novel approaches to validating hybrid classical + post-quantum cryptographic modules to FIPS 140-3 / CMVP across multiple hardware and OS targets from a single codebase. Validation is in preparation, not yet certified.
Secure, AI-native cryptographic compute that adapts across CPU SIMD paths (AES-NI, ARMv8) and GPU backends, choosing the fastest safe path for the workload without changing the security model.
Novel patterns for safe GPU-accelerated cryptography across the browser/WASM trust boundary and on constrained edge devices, designed so key material never crosses the boundary, with a tamper-evident trail for everything that does.
An experiment control plane that runs reproducible proof experiments across cryptography, machine learning, agents, trust and performance, with hash-chained, tamper-evident results anyone can inspect.
Every result is reproduced as a verifiable, hash-chained experiment before it ships, research you can independently re-run, not claims you have to take on trust.
R&D output isn't a demo; it lands in the shared cryptographic core that the platform and every Signet brand are built on.
We separate what's proven, what's in preparation, and what's still on the bench, and we never claim a certification we don't hold.
Quantum-safe, end to end.
TLS 1.3 hybrid key exchange, classical X25519 combined with ML-KEM, so connections resist harvest-now, decrypt-later attacks, with graceful fallback for legacy peers.
Decentralised identifiers and verifiable credentials signed with post-quantum signatures, with privacy-preserving selective disclosure, including verifiable identity for autonomous agents.
Quantum-resistant signing of software bills-of-materials with transparency logging, so provenance stays verifiable across decade-long lifecycles.
Algorithm-agnostic re-encryption and epoch re-keying for multi-decade retention, today's records survive tomorrow's standards.
Physics-based key distribution as a future key source (post-quantum cryptography always the fallback), and a quantum-native, Byzantine-fault-tolerant ledger for tamper-evident governance records.
Autonomy you can audit.
Language-model agents acting as a deliberative risk and governance layer, never on the latency-critical path, interpreting context and enforcing policy.
Instrumenting every decision so its full reasoning trace, attributions, context and counterfactuals, can be inspected and explained: from trust it to audit it.
High-fidelity generative simulations that rehearse strategies and policies across thousands of synthetic scenarios, including crises, before anything touches production.
Reasoning about interventions and counterfactuals rather than mere correlation, and privacy-preserving federated learning so a fleet improves together by sharing model updates, never raw data.
Machine-enforceable, version-controlled policy with human amendment and override, plus scoped, sandboxed, human-reviewed self-improvement, every autonomous capability with explicit escape hatches.
Long-horizon research into AI that operates as a governed legal-economic entity, and secure agent-to-agent settlement protocols.
Invent the site, don't template it.
Turning a screenshot, a screen recording, a wireframe or a design file into a working, production-ready site through vision-model decomposition.
Bounded, human-overridable AI agents that build, run and operate a site, autonomy without losing accountability.
Every design and content choice treated as a learned, evidence-weighted decision, with experiences that improve in real time from engagement signals.
3D and spatial interfaces, generative and data-driven visuals, motion and gamification as first-class design primitives.
Retrieval-augmented generation grounded in verifiable, provenance-tracked data, answers you can trace.
Built to grow without surprises.
Composable scaling, horizontal compute, read replicas, connection pooling, hot-path caching and columnar analytics, that grows throughput predictably while keeping latency low.
Precise, measurable thresholds that turn capacity decisions into observable, predetermined actions rather than guesswork.
High-ingest, columnar time-series storage for extreme-scale event workloads.
Durable workflow orchestration, unified observability and a zero-trust, defence-in-depth posture built on open standards.