AI reasoning
without the burn

Same model. Same answers. Smaller bill.

A deterministic hyper compute architecture for AI models and agents you already run

Talk to us See how it works
Your data Drift-free context Your AI model

AI models and agents on the platform

Your models reason over drift-free, validated context and spend fewer tokens

See how it works

Security and compliance

Each User's Virtual Organization is an isolated tenant running its own compute fabric on the platform, on premises or air-gapped

See how your data stays yours

Model builders

Validate training data, train and attest models through Big Bang, a dedicated API

Explore Big Bang

Works with the AI stack you already run

Model agnostic and hardware agnostic; see every integration
  • OpenAI
  • Anthropic Claude
  • Google Gemini
  • Meta Llama
  • Qwen
  • Mistral
  • Hugging Face
  • LangChain
  • CrewAI
  • NVIDIA NemoClaw
  • vLLM
  • AWS
  • Azure
  • Google Cloud
  • Cerebras
  • Groq

Built to make AI economically viable at scale

Data movement is a leading cost of running AI at scale; Axiom Vertex reduces the data transferred to find the context a model needs by hundreds to thousands of times per operation, depending on model size and hardware infrastructure

Data moved to find the context your model needs

Each depth layer adds one record to compare; conventional retrieval compares a full embedding vector per record, Axiom Vertex a 48-byte coordinate

Reasoning Model

See how an AI model reasons over drift-free context

Linear scale, adjusted to the selected model size. Conventional retrieval compares embedding vectors at 4 bytes per dimension; Axiom Vertex compares a 48-byte coordinate at every model size, measured in the platform's comparison-cost benchmark. One record per depth layer

From your data to context without drift

Your AI model still answers every request; the compute fabric supplies the validated context it reasons over

  1. 1

    Validate

    Every record enters through its ingest gateway, for federated, AI-generated or device-generated data, each with checks designed for what it validates. The root system laws, validation and dimensional, hold on every record; the platform is deterministic, so if any one law fails, the validation proof is rejected.

  2. 2

    Prove

    A record that passes receives its validation proof, an unforgeable, immutable, re-derivable mathematical identity, recorded on the Hypergeometric Ledger. The proof always produces the same content.

  3. 3

    Infer

    When your AI models and agents need context, the Relational Reasoning Model resolves each request on the compute fabric and the Geodesic Context Engine searches the hypervectors of the HyperVertex Ledger, returning every record with its validation proof. Your AI model reasons over drift-free context, every time.

Your data stays yours

Each User's Virtual Organization runs on its own dedicated hyperdimensional compute fabric, as an isolated tenant. Axiom Vertex enables your AI models to reason on that fabric, while your data stays in your own storage, sovereign to you

Your Virtual OrganizationIsolated tenant
AI models and agentsreason over drift-free context
Dedicated compute fabricfor your Virtual Organization
Data StorageSovereign for every user
  • Managed subscriptionVirtual Organizations support on-premises sovereign data storage, Cloudflare R2, AWS S3 and other approved cloud storage providers
  • On-premises nodesEdgeManager nodes with SPIFFE workload identity, outbound-only mTLS and a customer-run local coordinator
  • Air-gappedA Virtual Organization runs fully air-gapped, with identity and authorization verified locally

One Hub, spokes for every workload

Built for professional, business and enterprise workloads

Axiom

The core validation and proof pipeline

  • Ingress gateway with mandatory and industry-specific checks
  • Proof identity forged in StateFlow
  • Validation proofs committed to the Hypergeometric Ledger

Atlas

Spatial intelligence for AI models

  • High-dimensional hypervector encoding at any scale
  • Deterministic, reproducible context retrieval without drift
  • Hyperdimensional reasoning fabric with grounding for edge compute
  • Validation of AI-generated data

Cortex

Lifecycle management for autonomous and IoT devices

  • Fleet management through EdgeManager nodes
  • Validation of device-generated data for AI reasoning
  • Statistical baseline calibration for each organization's fleet

QI Encoder

Mathematically encodes and seals validation proofs

  • Unforgeable certification of every validated record
  • Seal receipts that verify independently
  • Zero-knowledge proof bridge for auditors and regulators

VX Convergence

Multi-domain consensus reasoning across all projects and services

  • Parallel reasoning across domains, merged into one answer
  • Measured agreement score on every result
  • One auditable consensus artifact per run
Dedicated API | Model Training | Attestation

Axiom Vertex Big Bang

General-purpose AI, from one agent to an agentic universe

A hosted service with its own API for training data validation, model training and attestation. Supports deterministic reasoning, billed per call, with a dedicated environment per user.

Talk to us about Big Bang

Training data validation

Every training record is validated before a model learns from it.

Model training and attestation

Models train on validated data and leave with an attestation bundle any party can verify.

Deterministic reasoning

Drift-free, re-derivable context keeps reasoning exact and economical at scale.

Zero trust from the network to the record

Zero trust access

Access follows NIST zero trust principles (SP 800-207), with multifactor login and workload identity.

Hardware-anchored signing

Keys are anchored in hardware (TPM 2.0, PKCS#11). Post-quantum signatures (NIST FIPS 204) are available.

AI governance

Maps to the NIST AI Risk Management Framework. Supports the EU AI Act and C2PA Content Credentials.

Enterprise controls

Controls that conform to SOC 2, ISO 27001, HIPAA and FedRAMP requirements. Every Virtual Organization runs as its own isolated tenant on its own dedicated compute fabric.

Integrations

Axiom Vertex supports the models, frameworks, clouds and hardware users choose today, and this list grows with them

AI models

Dedicated model API

  • OpenAI
  • Anthropic Claude
  • Google Gemini
  • Meta Llama
  • Qwen
  • Mistral
  • Hugging Face Inference API
  • Any OpenAI-compatible endpoint

Agents and orchestration

MCP

  • LangChain
  • CrewAI
  • NVIDIA NemoClaw
  • Claude agents
  • GPT agents

Inference and serving

Dedicated model API and REST

  • Fireworks
  • vLLM
  • TensorRT-LLM
  • NVIDIA Dynamo
  • SGLang
  • Ollama

Cloud and data

Storage silos and Agent Fetch

Storage silos

  • AWS S3
  • Cloudflare R2

Federated sources

  • Google Cloud Storage
  • Azure Blob
  • AWS S3
  • PostgreSQL
  • MySQL
  • REST APIs

Web bridges

  • Firecrawl
  • Bright Data
  • Apify
  • Tavily

Hardware

Exact integer arithmetic on every processor

  • CPUs
  • GPUs
  • NVIDIA on Dell Deskside GB10 and GB300
  • NVIDIA Jetson edge
  • Cerebras wafer-scale engines
  • Groq LPUs
  • SambaNova
  • Other ASICs

Developer

Build on the platform directly

  • REST API
  • MCP
  • WebSocket
  • Python SDK
  • TypeScript SDK
  • JavaScript SDK
  • Go SDK
  • Java SDK
  • C++ SDK
  • Kubernetes
  • WASM runtime

Frequently asked questions

Anything else, ask the team directly; book a conversation

What will happen with my context window?

Your model keeps its window and uses it for the request at hand. Your context stays in your own storage, and each request brings in the validated records it needs as drift-free context, so your model can draw on all of it, whatever the size of its window.

Do I need to change my AI model?

Your model stays as it is. Axiom Vertex works with ChatGPT, Claude, Gemini, Llama, Mistral, open models and your own; when your model needs data, your Virtual Organization's compute fabric supplies the drift-free context it reasons over.

Where does my data live?

In your own storage, sovereign to you. Your Virtual Organization runs on its own dedicated compute fabric, connected to where your data already is, such as AWS S3, Google Cloud, Azure Blob, PostgreSQL or MySQL; run it as a managed subscription, on your own nodes, or fully air-gapped.

Where does the saving come from?

Data movement is a leading cost of running AI at scale. Your Virtual Organization's compute fabric resolves the request and supplies only the records that answer it, so the model reads less and uses fewer tokens.

Will the context change between runs?

Same question, same context, every time; the context is re-derivable and without drift, so an AI model run with deterministic decoding returns the same answer. Each record carries a validation proof of where it came from and that it is unchanged.

Does it work with my tools?

Yes. It works with agent frameworks like LangChain and CrewAI, serving platforms like vLLM and Fireworks, and any OpenAI-compatible endpoint. We also offer REST, MCP and SDKs in six languages.

How do we start?

With a pilot in your own Virtual Organization. You run the same questions with and without Axiom Vertex and compare tokens, compute and accuracy, and see the saving before you sign.

An unassailable moat for your AI stack

Talk with the team about your models, agents, devices and data

Talk to us contact@axiomvertex.net