See it work

Proof you can run yourself

Everything on this page runs in your browser, on real outputs from the Axiom Vertex Reasoning Model. Ask the same question again, tamper with a record, follow a request through the platform.

Ask againTamper with a recordFollow a request

Proof you can run

Ask again. Same answer.

One question, run three times. Conventional retrieval can pull a slightly different set of records on each run, and the answer moves with them. Axiom Vertex returns the same validated records every time, so the AI model reasons over drift-free context and, with deterministic decoding, returns the same answer.

ExampleFinance case from the Axiom Vertex Reasoning Model. Both lanes use the same AI model, Qwen2.5‑0.5B‑Instruct.
Question

On what date was invoice 4471 paid?

Run 1 of 3
Conventional retrievalApproximate search; ranking and versions vary
    Answer
    context hash
    Axiom VertexValidated records, independent path
      AnswerApril 9Same validated records, every run
      context hash d2b69aaecd4b4ed5
      identical across runs
      87% Chance of at least one wrong step, 1 − 0.99steps

      Verifiable

      Every record carries its proof

      When a record is validated, Axiom Vertex forges its datum, the validation proof. The datum is immutable, carries its entry in the validation history, is sealed by its Merkle proof and is committed to the Hypergeometric Ledger. Its coordinates never drift, so the same coordinates always return the same content. The seal binds the record's hash, so a record that no longer matches its committed proof is detected when the platform verifies it.

      Try itChange a single character. The demo uses SHA-384, a standard 48-byte hash computed in your browser, to show the principle.
      Stored proof · 48 bytes
      Computed now
      Proof matches. Record accepted.

      Integration

      Keep your models. Keep your hardware.

      Your app calls your AI model exactly as it does today. When the model needs data, the dedicated compute fabric of your Virtual Organization resolves the request and supplies only the validated records it needs, as drift-free context, so each answer uses fewer tokens.

      Works with any model
      ChatGPTClaudeGeminiLlamaQwenHugging FaceYour own
      Your data stays where it is
      AWS S3Google CloudAzure BlobCloudflare R2PostgreSQLMySQLOracleSQL ServerSQLiteNoSQL databasesVector databasesData warehousesTime-seriesREST APIs
      Your app or agentSends a request to your model, as it does today
      1 · request
      5 · response
      Your AI modelAny model, unchanged
      2 · asks for data
      4 · drift-free context
      Your Virtual Organization's compute fabricDedicated to one Virtual Organization; isolated tenant; air-gap ready
      Relational Reasoning ModelResolves the request into coordinates on the compute fabric and decomposes it into sub-queries
      Geodesic Context EngineSearches the HyperVector Ledger, ranks candidates and assembles the drift-free context for your model, with a validation proof for each record
      HyperVector LedgerHyperdimensional vectors encoded from your validated records, used to search them
      Hypergeometric LedgerRecords every validation proof; proves where each record came from and that it is unchanged
      3 · resolves the records it needs
      Your dataSovereign to you; content stays in your storage