AI Infrastructure · Platform Engineering · London
Most AI can't show its work.
We build systems that can — cryptographically, from the supply chain to the signed decision. Platform engineering for teams running AI in production: BentoML, Firecracker, NATS, SeaweedFS, Azure Cognitive, Kubernetes and Envoy — and products built on the same provable substrate, starting with Consensus.Services.
▸ New · Consensus.Services — group decisions you can prove
Provable computing · open source + products
The fleet.
A full-stack provable computing platform — from attested supply-chain artifacts, through semantically governed data inside stock PostgreSQL, to signed, machine-readable decision events. The thread — what was built, from what, and what it decided — runs from the silicon to the application. No one else in this niche holds that chain end to end.
SPARQL 1.1, SHACL Core (25/25 W3C tests) and OWL-RL — inside stock PostgreSQL. Benchmarked at 8.2 billion triples and 466K writes/s. MIT open source.
A Concept Kernel that makes ungoverned writes structurally impossible — one-door dispatch, a strict role floor, and an HMAC/ed25519 proof-chained ledger.
Ontology-first OCI bundle assembler. Every artifact ships with an RDF bill of materials — verifiable with a single command.
Timed group decisions where every outcome emits a signed, ontological proof — built on pgCK and pgRDF.
In production
Live examples.
Working deployments you can inspect right now — public proof of what our platforms do in anger.
01 / 05
Lab Console
Operator console for the NeuxScience Adaptive Dispatcher — an n-back task-difficulty prediction service. Live BentoML 1.4 deployment you can drive yourself.
02 / 05
Tileformer
A browser-based tile and keyframe animation sequencer for authoring visual experiments in cognitive psychology — 16×12 grid, layers, timeline scrubbing, frame-accurate stimulus composition.
03 / 05
Concept Kernel
A published Turtle/OWL ontology corpus for sovereign AI kernels — BFO-grounded identity, PROV-O provenance, SHACL constraints, ValueFlows economics. Currently v3.5-alpha6.
04 / 05
TTS Render Gallery
30 F5-TTS renders from the A100 serverless batch pipeline — voice-clone reference clips, style axes, cost-per-batch receipts. Local authoring tool; public capability lives on /tts/.
05 / 05
Evolution Engine
Firecracker-backed autonomous self-improving workflows — continuous micro-reasoning passes against LLMs composed from node-based 'concept kernels' (OODA · TEXT · LLM · PICK-1 · FIFO · MULTI). Minimal-token 'caveman' query shape for high-throughput, low-cost iteration.
Platform engineering
Expertise.
The disciplines beneath the fleet — each a deep specialism, each deployable in anger. We build platforms the way we build bridges: with engineering, not aspiration.
01 / 08
BentoML Model Serving
Production inference with autoscaling, A/B testing, and cost-performance tuning.
02 / 08
Firecracker MicroVM Isolation
Per-tenant sandboxing for untrusted workloads at VM speed.
03 / 08
NATS Messaging Fabric
JetStream persistence, KV store, and object store for event-driven systems.
04 / 08
SeaweedFS Storage
Block and object storage, S3-compatible, with a small operational footprint.
06 / 08
Platform Materialisation
Umbrella offering: Kubernetes control planes and Envoy Gateway — the foundation beneath everything above.
07 / 08
Concept Kernel · Ontologies
A Turtle/OWL ontology corpus for sovereign AI kernels — identity, provenance, governance, grounded in BFO and PROV-O.
core.ttlproof.ttlrbac.ttlprocesses.ttlself-improvement.ttl08 / 08
TTS & Voice Cloning
Multi-model speech synthesis (Parler · CosyVoice 2 · F5 · Dia · StyleTTS 2) plus voice cloning, queued on Azure A100 serverless — $0 idle between batches, manifest-driven provenance for every render.
parlercosyvoice2f5diastyletts2Method
How we work.
Every engagement — Assignment, Workshop, Audit, Architecture — follows the same three-part contract. No open-ended retainers, no scope that grows on its own, no invoices for ambiguity.
Scope
One capability, one outcome, one SLA. We agree the boundary before we start and write it into the engagement brief. Out-of-scope asks become a separate, priced follow-up — never absorbed silently.
Timeline
Engagements are time-boxed (1 day / 3 days / 1 week / 2 weeks depending on SKU). You get a calendar with start / end dates and a daily check-in cadence. Delays caused on our side reset the clock; delays on yours pause it.
Deliverables
Every engagement ships a working artefact (running code, a configured cluster, a measured benchmark) plus a written memo you can hand to a colleague. No engagement ends with "it's all in our heads."
Proof
Selected engagements.
Neux Ltd has been running platforms for enterprise and public-sector clients since 2014. A selection of concrete outcomes:
About
Who you're hiring.
Neux Ltd is led by Peter Styk — platform architect and principal since 2014 (LinkedIn). A decade of platform engineering at the intersection of event-driven architecture, zero-trust identity and sovereign infrastructure — deepened over the last three years into AI-native systems: knowledge graphs, structured reasoning, and agentic coordination on privately hosted open-source ML. The provability thesis came from a simple question: what does automation look like when it has to show its work, not just produce output? Our sister brand neux.ai covers the AI-consultancy work that doesn't belong on a platform-engineering site.
Available for
Work with us.
A decade of platform engineering, deepened into AI-native systems. If your organisation needs its automated decisions to be auditable — not just fast, we'd welcome the conversation.
Across
Start a conversation →Microsoft Cloud AI Partner · neux.io
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Book a call.
No sales funnel, no gated download, no tracking pixels. Two or three sentences on the problem is enough for us to prep. Replies within 2 working days.
Neux Ltd
AI Infrastructure · Platform Engineering · London.
Since 2014.
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