Q&A with Subodh Shetty, CTO of Cintara
Short Bio
Subodh Shetty is the Chief Technology Officer of Cintara, where he leads the design and implementation of the company’s agentic AI-native blockchain. With over two decades of experience in software engineering, enterprise architecture, and AI/ML applications, Subodh has built and scaled products for startups and major corporations, including Amazon. He brings deep expertise in distributed systems, fintech innovation, and cloud-based infrastructure, and is passionate about combining blockchain with artificial intelligence to create secure, intelligent networks that solve real-world problems.
1. You describe your platform as the first agentic AI native blockchain. How should non-technical readers understand this?
Most blockchains are simply distributed ledgers, they store transactions but do not process them intelligently. Cintara changes that by embedding AI directly into the network. Instead of merely recording that a transaction occurred, Cintara’s AI agents can analyze it in real time, for example checking whether it looks fraudulent before it is approved.
Think of Cintara as a blockchain with an AI co-pilot. It does more than just keep records: it can solve problems, optimize gas fees, detect fraud, and even trigger compliance checks, all automatically and natively within the network.
2. Can you explain the agent registry: how it works and why it matters?
The agent registry is a directory of all AI agents operating on Cintara. When enterprises or developers onboard agents, for tasks such as fraud detection, translation, or document verification, Cintara automatically registers them on-chain.
Registration includes ownership details, descriptions, and usage parameters. This makes agents discoverable and callable by anyone, with payments and permissions handled natively by smart contracts. It works much like an app store, except instead of apps, it lists verified AI agents that run securely and transparently on the blockchain.
3. How does the decentralized compute marketplace function, and what makes it different from centralized alternatives?
Cintara allows anyone to rent AI power directly from the blockchain. Its validators don’t just secure transactions; they also contribute GPU and CPU capacity that can be used to run AI tasks. Developers or enterprises can request tasks like text analysis, which are distributed across validator nodes.
Validators are rewarded in Cintara tokens for both securing the chain and running these workloads. This creates a flywheel where network usage drives validator incentives and token utility, all in a decentralized and trustless way, unlike centralized cloud providers where users must trust a single company.
4. You mention a validator network optimized for AI. What does this enable that current blockchains do not?
Traditional blockchains can only record data; Cintara’s validator network can process and verify it in real time. For example, in healthcare, Cintara validators could check patient records for correct formatting, anonymization, and compliance before approving them on-chain.
This creates an active, intelligent ledger, one that can run machine learning inferences, trigger compliance agents, and maintain full auditability and transparency. In short, it transforms blockchains from passive record-keepers into proactive problem-solvers.
5. How does on-chain KYC/AML enforcement work?
KYC begins with external identity verification through trusted providers. Users submit documents, which are checked for sanctions, scanned, and matched biometrically. The provider then issues a digital credential.
Cintara never stores private documents; it simply receives a wallet address and a confirmation that the user is verified. A zero-knowledge proof (ZK proof) is posted on-chain, allowing validators to enforce compliance without revealing personal information. This approach ensures privacy while maintaining regulatory integrity.
6. How does your collaboration with Secret Network strengthen your privacy and security offering?
Secret Network provides Trusted Execution Environments (TEEs) that allow AI models to run securely in encrypted environments. Combining Cintara’s AI-native blockchain with Secret’s confidential computing ensures that sensitive data, such as healthcare or financial information, is processed privately, even from validators themselves.
A proof of concept is already running, where validator nodes with embedded LLMs operate inside Secret’s secure VM. This guarantees that computations remain confidential, enabling privacy-preserving AI use cases for highly regulated industries.
7. What safeguards make Cintara more resilient for enterprises and Web3 developers?
Cintara provides confidentiality via TEEs, compliance enforcement via ZK proofs, and real-time validation through its AI-enabled network. The platform is fully auditable, so enterprises can verify what agents did at any point, making it ideal for mission-critical sectors such as trade finance, healthcare, and tax compliance.
8. Could you share more about your early customer partnerships?
One of Cintara’s first partnerships is with Drip Capital, a leader in global trade finance. Drip Capital advances payments to small and medium-sized exporters even before goods are shipped, but international trade remains paper-heavy and prone to delays.
By using Cintara’s AI agents, Drip Capital aims to streamline KYC/AML verification, improve transparency, and reduce settlement friction. The result is faster processing, fewer disputes, and stronger compliance, all of which directly benefit their customers.
Cintara is also working with a healthcare company exploring AI-enhanced blockchain for patient data management, and another company using blockchain data to generate tax documents directly.
9. How do your leadership team’s backgrounds shape the project?
Cintara’s founding team has over 20 years’ experience each in enterprise technology, AI, and blockchain:
- Sam (CEO) sets the strategic vision for combining AI and blockchain.
- Subodh Shetty (CTO) ensures the technical foundation is robust, selecting the right chain, validator design, and architecture.
- Minhaj Arifin (COO) focuses on execution, community growth, and smooth validator onboarding.
- Greg Adams (CCO) drives go-to-market strategy, enterprise positioning, and investor relations.
Together, they provide a balance of vision, technical execution, operational delivery, and commercial focus.
10. What advantages come from having the core team based close together?
The team lives within minutes of each other, allowing frequent in-person meetings and informal collaboration, often over barbecues and dinners. This builds trust, accelerates decision-making, and creates a shared culture that is rare in Web3, where most teams are globally distributed and remote.
11. How are you balancing having both doxxed and non-doxxed members?
Most of the leadership team is fully doxxed. Sam, the CEO, is known and present in professional and VC circles, even if his LinkedIn update is pending. This provides credibility and trust while maintaining flexibility during the transition period.
12. Can you provide insight into your ideal first users?
Ideal early users include both Web2 enterprises seeking compliance-friendly blockchain solutions and Web3 developers who want to deploy AI agents in a secure, decentralized way. Enterprises can leverage Cintara for fraud detection, KYC, and data compliance, while developers gain a platform to host, monetize, and run their AI models natively on-chain.
13. Can you give an example of a concrete use case expected soon?
The Drip Capital pilot is the clearest near-term example, using Cintara to automate trade finance verification. Additional examples include healthcare data compliance checks and automated tax document generation from on-chain transactions.
14. How do you envision scaling adoption?
The roadmap includes:
- Completing the agentic AI marketplace on testnet by late October or early November.
- Signing more Letters of Intent (LOIs) with enterprises.
- Showcasing working pilots like Drip Capital to generate a flywheel effect.
- Partnering with consultancies to integrate Cintara into enterprise workflows.
As more agents and enterprises join, network effects will drive token usage and validator participation, accelerating growth.
