Vishwa

Vishwa is an execution control layer for AI-driven finance. It does not manage funds directly but acts as a gatekeeper: before an AI agent executes a trade, Vishwa verifies the request against predefined rules inside a Trusted Execution Environment (TEE). Users interact via the Vishwa CLI, describing intent in plain language, and the system checks authorization, solvency, and transaction limits before allowing execution.

The core problem it solves is that traditional wallets or trading strategies cannot validate an AI agent's intent before funds move. A bug or hallucination could cause the agent to transfer assets incorrectly. Vishwa's pre-execution verification ensures agents only act within user-set boundaries, while keeping an auditable record of every authorization.

Its competitive edge lies in TEE-based pre-execution checks, non-custodial design, and a product ecosystem including Veta (control layer), PredX (agent-native financial actions), and Naro (expanded use cases).

Over the past six months (2026-02-28 to 2026-08-31), Vishwa rebranded to VishwaLab in June, shifting from a single product to a broader ecosystem. The CLI launched in June. In May, it participated in Pharos' "Building the RealFi Stack" event and advanced collaborations with ZIA Finance and Valimar Finance. By end-June, it reported over $170M in capital under enforcement, deployed on Solana, Base, and Pharos. It also published technical articles, including "Agents Can Move Money" and "Agent-Native Banking."

Caveats: the project is still early-stage, ecosystem scale remains limited, and reliance on TEE technology introduces potential technical risks.