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DeepSafe Gets $3M Backing From Antalpha and Spark Digital Capital

By

Shweta Chakrawarty

Shweta Chakrawarty

DeepSafe, a decentralized AI verification network, secured $3M in seed funding from Antalpha to develop its secure AI systems.

DeepSafe Gets $3M Backing From Antalpha and Spark Digital Capital

Quick Take

Summary is AI generated, newsroom reviewed.

  • DeepSafe raised $3 million in seed funding led by Antalpha Ventures and Spark Digital Capital.

  • The company is building a decentralized verification layer for AI trust and accountability.

  • Its CRVA algorithm uses Ring-VRF, ZKP, MPC, and TEE to enable multi-agent, tamper-proof verification.

  • DeepSafe plans to expand research and developer onboarding to create a new AI verification standard.

Decentralized AI verification network DeepSafe has secured $3 million in seed funding from major investors. That includes Antalpha Ventures and Spark Digital Capital. The funding marks a strong vote of confidence in DeepSafe’s mission to make artificial intelligence systems. Which is more transparent, secure and verifiable.

A Push for Trust in AI

AI systems are rapidly evolving, but trust remains a major concern. DeepSafe aims to fix that by building a decentralized verification layer. That confirms whether AI behaviors align with human intended actions. The startup’s technology ensures that AI models don’t act outside their ethical or operational boundaries.

By combining cryptographic techniques with decentralized governance. Therefore, DeepSafe wants to make sure that “trust” isn’t something users have to give. Rather, it’s something they can verify. Ultimately, the company’s approach is designed to strengthen accountability and reliability across AI applications.

Cutting-Edge Cryptography Behind DeepSafe

At the core of DeepSafe’s innovation lies its CRVA decentralized verification algorithm. This integrates four advanced cryptographic technologies: Ring-VRF, Zero-Knowledge Proofs (ZKP), Multi-Party Computation (MPC) and Trusted Execution Environments (TEE).

This combination enables dynamic random selection of verification nodes and multi-agent collaborative verification of AI behavior. Thereby, essentially creating a digital jury system for AI actions. Furthermore, the model allows on-chain and off-chain message verification. Which ensures that AI outputs can be independently validated by multiple participants. Rather than a single central authority.

This blend of privacy, randomness and decentralization makes the network resistant to manipulation while maintaining verifiable transparency. The technology has already attracted recognition from the global academic community. DeepSafe’s core protocol has been accepted for publication in the prestigious IEEE Transactions on Information Forensics and Security (TIFS). Under document ID 9903072, a noteworthy achievement for a project still in its early stages.

Building a Global Verification Network

DeepSafe’s progress isn’t just theoretical. The platform has already verified nearly 120 million transactions and boasts more than 2.65 million active accounts. These figures highlight growing interest from AI developers and blockchain enthusiasts who see value in a trust-anchored verification layer.

The company’s decentralized structure allows any qualified node to join and participate in verification. This creates a distributed system that scales with user growth. The collaborative model rewards accuracy and transparency. While discouraging manipulation through built-in cryptographic safeguards.

Backed by Industry Leaders

The seed round, led by Antalpha Ventures and Spark Digital Capital. Consequently underscores rising investor confidence in the intersection of AI and Web3. Furthermore, both firms have a track record of backing infrastructure projects. That pushes technological boundaries.

With this funding, therefore, DeepSafe plans to expand its research partnerships. This refines its CRVA protocol and consequently onboards more developers into its ecosystem. Ultimately, the goal is to build a verification standard that could be adopted across multiple AI and blockchain industries. Ranging from finance and robotics to content generation and cybersecurity.

Looking Ahead

As AI becomes deeply integrated into everyday systems. Consequently, the need for trust and verification grows urgent. In this light, DeepSafe’s model offers a decentralized, tamper-proof way to ensure that AI acts as intended. With no hidden biases and no untraceable decisions.

The project’s combination of advanced cryptography, strong academic validation and early network adoption. Therefore, positions it as a potential cornerstone in the movement toward trustworthy AI. Furthermore, with $3 million in new funding and the backing of established crypto venture firms. DeepSafe is stepping into a leadership role in shaping how the world verifies intelligence, human and artificial.

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