Multi-model databases and foundational infra for agentic, on-device, and peer-to-peer AI

The rise of multi-model data platforms and foundational infrastructure is fundamentally transforming how autonomous, agentic AI systems are built, deployed, and managed. Recent funding milestones, innovative startups, and strategic acquisitions highlight a clear industry trend towards developing robust, scalable, and flexible layers that underpin next-generation autonomous agents.

Central to this evolution is SurrealDB, a London-based, multi-model, AI-native database platform that has recently secured an additional $23 million in a Series A extension, bringing its total funding to $38 million. As Chief Product Officer Jane Doe explains, the company's focus is on providing the infrastructure that autonomous AI agents need to operate efficiently at scale. With enhanced multi-model support—integrating structured, semi-structured, and unstructured data—SurrealDB aims to enable agents to access rich, contextual information, facilitating more nuanced reasoning in complex environments like finance, healthcare, and logistics.

This investment underscores a broader industry momentum where multi-model data platforms are becoming the backbone of autonomous, agentic AI systems. The ecosystem is rapidly expanding, with startups and initiatives contributing to this infrastructure shift:

• Potpie, which has raised $2.2 million in pre-seed funding, is developing a ‘knowledge graph for code’ designed to improve AI agents’ understanding and usability.
• Hypercore, with $13.5 million in Series A funding, is focusing on industry-specific autonomous agents, including AI-powered administrative tools tailored for private credit markets.
• Jump, recently securing $80 million in Series B funding, is building an AI operating system for financial advisors, aiming to automate routine tasks while integrating seamlessly with existing data ecosystems.
• Union.ai completed a $38.1 million Series A, providing tools to streamline AI development workflows, ensuring reliability and scalability.
• Arize AI, with a $70 million Series C, emphasizes AI reliability and monitoring, crucial for trustworthy autonomous deployments.

Strategic acquisitions further reinforce this trend. Notably, Anthropic’s acquisition of Vercept—a startup specializing in tools for multi-step reasoning, planning, and decision-making—signals an industry move toward building higher-order, sophisticated agents capable of complex cognition.

In addition to data management and reasoning, foundational infrastructure layers such as peer-to-peer (P2P) agent infrastructure and on-device AI frameworks are gaining traction. Unicity Labs, which raised $3 million in seed funding, is developing decentralized P2P infrastructure to support resilient autonomous AI interactions, enabling systems to operate without centralized dependencies. Similarly, Mirai, with $10 million in seed funding, is advancing on-device AI frameworks optimized for real-time, privacy-preserving operations on edge devices, vital for applications requiring low latency and high privacy standards.

The importance of memory and data management is also recognized. Cognee, based in Berlin, secured $7.5 million in seed funding to develop infrastructure focused on persistent memory, allowing AI systems to retain context over longer interactions and operate effectively in resource-constrained environments. Such capabilities are essential for personalized, long-term AI experiences.

Moreover, LLMOps platforms like Portkey, which raised $15 million, are critical for scaling and managing large language models in production, ensuring reliability and efficiency—key for enterprise-grade autonomous AI deployments.

Collectively, these developments highlight a market-wide shift toward building trustworthy, scalable, and flexible infrastructure that supports autonomous decision-making. The convergence of funding, strategic M&A activity, and innovative startups signals that multi-model, agent-oriented platforms are increasingly viewed as the core foundation for the AI systems of the future.

In summary, the industry is moving toward an ecosystem where robust data platforms, decentralized communication layers, on-device frameworks, and persistent memory systems work in concert to enable reliable, scalable, and sophisticated autonomous agents. SurrealDB's recent funding and platform updates exemplify this trajectory, positioning it as a key player in shaping the infrastructure that will power next-generation autonomous AI applications across industries. As these layers mature, they will unlock new possibilities for intelligent automation, real-time edge processing, and complex reasoning, ultimately transforming how autonomous systems are built and operated at scale.