Commvault partners with Pinecone to strengthen cyber resilience for enterprise AI workloads

Commvault has announced a strategic partnership with Pinecone aimed at strengthening cyber resilience for enterprise artificial intelligence environments, as organisations increasingly rely on vector databases to power retrieval-augmented generation and other production AI use cases. The collaboration is designed to help enterprises protect, govern, and rapidly recover vector retrieval workloads that have become central to modern AI stacks, particularly in regulated and security-sensitive industries.

As AI adoption accelerates across sectors such as finance, healthcare, government, and large-scale digital services, enterprises are moving beyond experimental pilots towards always-on AI systems that support mission-critical operations. These systems rely heavily on vector databases, which store numerical representations of data used by AI models to retrieve relevant information during inference. While these databases are built for performance and scale, enterprises have faced growing concerns around resilience, governance, and recovery when these vector workloads are compromised or corrupted.

The partnership brings together Commvault’s cyber resilience platform with Pinecone’s vector database technology. Together, the two companies aim to provide joint customers with additional layers of protection that extend beyond native durability, allowing organisations to apply the same recovery, compliance, and governance standards used for traditional enterprise data to AI-driven workloads.

Addressing resilience gaps in vector-driven AI systems

Vector databases sit at the core of many modern AI architectures, enabling models to quickly retrieve relevant context from large knowledge bases during training and inference. These databases store vector embeddings that represent relationships between text, images, and other data types, making them essential for accurate and context-aware AI responses. As retrieval-augmented generation becomes a common approach for improving model reliability, the integrity and availability of vector data has become increasingly critical.

Despite their importance, enterprises with strict compliance and governance requirements have had limited options to safeguard vector data against threats such as corruption, accidental deletion, or malicious attacks. While Pinecone provides natively durable storage and built-in backups, many organisations require additional controls to meet internal risk policies and external regulatory standards.

The new solution addresses these challenges by extending Commvault’s cyber resilience capabilities to vector retrieval workloads. This includes immutable backups, point-in-time recovery, and configurable extended retention for vector data, all designed to operate without affecting query latency. By integrating these capabilities with Pinecone’s platform, enterprises can better protect the data that underpins their AI systems while maintaining performance at scale.

Commvault delivers the solution through its cloud-native platform, supporting deployments across Amazon Web Services, Microsoft Azure, Google Cloud, and multi-cloud environments. This unified approach is intended to simplify resilience operations for organisations running AI workloads across multiple cloud providers, reducing fragmentation and operational complexity.

Protecting AI workloads against emerging cyber threats

As AI systems become more deeply embedded in business processes, they are also becoming more attractive targets for cyber attacks. Threats such as data poisoning, evasion attacks, privacy breaches, and malicious data injection pose significant risks to AI models and the outputs they generate. In vector-driven systems, even subtle corruption of embeddings can lead to degraded performance, inaccurate responses, or unintended behaviour.

The Commvault and Pinecone integration is designed to help organisations respond to these risks by enabling secure recovery of vector indexes to a known good state. Point-in-time recovery allows enterprises to roll back vector data to a previous version, helping to minimise downtime and preserve the quality of AI inference. Backups are stored as encrypted, air-gapped, and immutable copies, supporting clean recovery even in the event of ransomware attacks or insider threats.

By applying these protections to vector workloads, enterprises can treat AI systems with the same level of operational discipline as other mission-critical applications. This is particularly important for organisations operating in regulated environments, where auditability and data integrity are essential.

Pranay Ahlawat, Chief Technology and AI Officer at Commvault, said the partnership reflects a growing need for stronger safeguards as AI moves into production environments. “As enterprises embed AI deeper into their operations and leverage RAG, the vector database layer has become mission-critical; increasingly, these organisations seek additional layers of protection and compliance beyond their already highly durable systems. With Pinecone, we are closing that protection gap,” he said. “We’re enabling AI stacks to operate with the same confidence, governance, and recoverability that traditional workloads demand.”

From Pinecone’s perspective, the partnership adds another layer of assurance for customers managing complex AI deployments. Jeff Zhu, Vice President of Product at Pinecone, said, “Pinecone is built for performance and scale, and our customers trust us with their most critical AI assets. Partnering with Commvault allows us to offer an even deeper level of resilience for organisations with complex compliance needs.”

Enabling production-ready AI with governance and compliance in mind

Beyond recovery and threat protection, the joint solution is positioned to help enterprises meet governance, regulatory, and audit requirements that are increasingly applied to AI systems. Many organisations are under pressure to demonstrate how AI data is stored, protected, and recovered, particularly as regulations around data protection and AI accountability continue to evolve.

By maintaining indelible and auditable copies of vector data, the Commvault and Pinecone solution supports compliance workflows and provides greater visibility into AI data management practices. This can be especially important for enterprises seeking to move retrieval-augmented generation systems from proof-of-concept projects into production environments that support customer-facing or revenue-generating applications.

The companies position the solution as a way to elevate AI systems to enterprise-grade standards, ensuring they are resilient, governed, and recoverable by design. This approach reflects a broader shift in how organisations view AI infrastructure, no longer as experimental technology, but as a core part of the enterprise IT landscape.

The integration between Commvault and Pinecone is targeted for general availability globally in the first half of 2026, giving enterprises time to evaluate how enhanced resilience for vector workloads fits into their broader AI and cyber security strategies.