@withveya

🚨 VEYA PRODUCT DEMO IS LIVE What happens when an AI agent goes rogue? As Agentic AI gains access to money, data, and real-world systems, boundaries and verification matter. VEYA addresses this with controlled environments, sealed execution, and verifiable on-chain proof. Environment → Agent → Sealed Run → Validator Quorum → Settlement A real product workflow running on Robinhood Chain testnet (46630). AI agents need boundaries. AI actions need verification. 🎥 Watch VEYA being built in public.

VEYA Product Demo goes live in 2 hours. From creating an environment to deploying an agent, running sealed execution, and settling a verifiable result on Robinhood Chain testnet (46630). This is the actual product workflow not a concept or mockup. See how VEYA brings together boundaries, execution, and on-chain proof. Built on testnet. Built in public. Stay tuned.

Build in public at VEYA. (BiP) A big part of building infrastructure is making failures understandable not just making the happy path work. Today’s progress: 1. Real operations, real attestations. We ran all three daily workflows using actual payloads: private inference, multi-validator compute, and policy tool calls. Successful and denied calls produced the expected digests and on-chain attestations. 2. Fail-closed errors that actually help. When multi-validator compute was refused, the interface suggested adding tools the agent already had. The explanation now uses the same allowlist as the execution check, keeping the message aligned with the actual policy. 3. Agent permissions are now editable. Tool access was previously fixed at deployment, even though the API supported updates. Agents now have an Edit tools control, with the same validation applied to new and updated grants. Wildcard permissions remain blocked. 4. Runtime errors explain what went wrong. We fixed two confusing failures: i)Payload shape errors now identify and correct the wrong request format. ii)The hash tool reports which keys it received without exposing their values. The goal isn't just to make agents execute. It's to make execution understandable, controllable, and verifiable. VEYA. Infrastructure for autonomous systems.

We are live on https://t.co/0n4Ogv8le6

3/8 Verifiable Inference Environment Private inference with a green check and no details isn't enough. You should be able to ask: Where did my work actually run? Not just: Private inference: ✓ But evidence you can actually inspect: Inference Environment Provider: Confidential Compute Workload ID: … Attestation: Verified Model Hash: … Runtime Measurement: … Key Binding: Verified Request Nonce: … Status: VALID Because when you send sensitive work for protected processing, you need more than a privacy claim. You need to know: → what environment handled it → what software was authorized to run → whether the runtime was verified → whether the keys matched the session → whether the evidence is bound to your request A hash alone isn't the whole story. The environment matters. The execution matters. The evidence matters. When agents handle sensitive work, trust shouldn't be a label. Trust is evidence. VEYA. Private inference you can inspect.