ZeroByte.AI

Singapore · AI trust infrastructure

Privacy by architecture.
Governance by design.

ZeroByte.AI builds the trust layer that lets regulated financial institutions run AI agents: zero bytes of client data touched, zero actions outside governance.

We build the runtime governance layer that lets banks, accounting firms, and wealth managers put AI agents to work inside regulated environments.

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Our name is our architecture promise: the amount of your data we can touch is zero bytes.

The problem

Two requirements for agents in regulated work.

Regulated institutions face two fears that cancel out the value of AI agents: data walking out the door, and agents acting without oversight. Most vendors answer with promises. Contracts say the data will not be read; dashboards say the agent behaved. Neither survives a serious audit, because promises are policy and policy can fail silently.

Our answer is architectural. ZeroByte.AI turns both fears into verifiable properties of the system.

Zero-byte leakage

Client data stays inside the client's boundary.

Sensitive content is protected through per-tenant envelope encryption, PII detection and masking before any external model call, and re-insertion of real values only inside the client boundary. In sovereign deployments, both the model and the agent platform we designed run locally on hardware the client owns. Confidential content has no egress path at all.

Keys never leave the client's control, and no content crosses the perimeter. This is data minimization enforced by design rather than by policy.

Zero-bypass governance

Every agent action passes through an execution gate.

This is the SAFR checkpoint in production. Every agent has an identity. Every human instruction is signed. The policy rulebook is built with the chief compliance office up front, before any agent is allowed to act.

Verification is the work that matters: in the Disposition Engine, a verification agent powered by a local model checks each proposed action against that rulebook, precisely and at runtime speed. Approval is cryptographically bound to execution. Without a signed disposition, the action cannot run. Policies are tighten-only: controls can become stricter over time, never quietly looser.

Evidence

Deciding and recording are the same act.

Each action produces a five-segment evidence chain, covering instruction, policy, proposal, disposition, and execution receipt, with every segment signed by its own authority. The audit trail has no gaps to explain.

  1. 01 Instruction
  2. 02 Policy
  3. 03 Proposal
  4. 04 Disposition
  5. 05 Execution receipt

Every segment signed by its own authority.

Deploy

The trust layer above the runtime. The application layer is untrusted by design.

ZeroByte.AI operates as the trust, identity, and audit layer on top of production agent runtimes, including Google Agent Engine and AWS Bedrock AgentCore. Institutions choose the boundary that fits their risk appetite, from a managed cloud deployment to a fully sovereign, air-gapped installation where both the model and the ZeroByte.AI agent platform run locally on client-owned NVIDIA DGX Spark and NVIDIA DGX Station systems.

Managed cloud Sovereign, air-gapped

Runtime

  • Google Agent Engine
  • AWS Bedrock AgentCore

Local inference

  • NVIDIA DGX Spark
  • NVIDIA DGX Station

Built for the regulator in the room

Designed in direct alignment with SAFR.

ZeroByte.AI is designed in direct alignment with SAFR (Safeguards for Agentic Finance at Runtime), the framework for governing AI agents in finance published in July 2026 by the Monetary Authority of Singapore together with leading financial institutions and FinTechs under MAS's BuildFin.ai initiative. SAFR addresses a problem regulators consider urgent: agents now act at a speed and scale beyond practical human intervention, so governance must move to runtime, where every proposed action is verified against predefined mandates, policies, and risk boundaries, and recorded, before it executes.

  • 01 Agent identity
  • 02 Controls repository
  • 03 Disposition engine
  • 04 Tamper-evident audit log

This is precisely the architecture ZeroByte.AI ships. Agent identity, a signed instruction, and a compliance-authored rulebook sit in front of every action. Our execution gate is a SAFR governance checkpoint. In the Disposition Engine, a local-model verification agent implements policy-bound execution: precise, and fast enough to live on the runtime path. Our five-segment evidence chain is the tamper-evident audit log the framework calls for. Data handling follows the same first principles, with minimization consistent with PDPA and GDPR.

Our position with compliance teams is simple to state and simple to test. Other platforms promise they will not misuse your data. ZeroByte.AI is built so that we cannot.

SAFR is a proposed framework published by MAS with industry participants under BuildFin.ai. It is not regulatory guidance, supervisory expectations, or a certification scheme. References describe design alignment. They do not imply that MAS, BuildFin.ai, or any SAFR contributor has reviewed, certified, endorsed, or approved ZeroByte. ZeroByte is an independent company and is not affiliated with the Monetary Authority of Singapore.

Company

Founded in Singapore.

ZeroByte.AI (Zero Byte Labs Pte. Ltd.) is a Singapore-based AI trust infrastructure company. ZeroByte.AI was founded in Singapore by a team with doctoral-level cryptography and distributed systems expertise, prior work with financial regulators, and teaching affiliation with the National University of Singapore.

Registered office

Zero Byte Labs Pte. Ltd.

71 Robinson Road

Singapore 068895

Briefing

For institutions that cannot take policy as proof.

Institutional briefings for banks, accounting firms, and wealth managers.