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Archestra raises £2.5m to protect corporate data from AI agents

The round was led by VC firm Concept Ventures

Archestra
Archestra co-founders Matvey Kukuy (CEO), Ildar Iskhakov (CTO) and founding engineer, Joey Orlando. Image credit: Archestra.

Archestra, a London-based startup connecting AI agents to company data, has secured a £2.5m funding round.

An open-source platform, Archestra is designed to introduce security layers to allow companies to adopt new AI tools with access to their data.

Businesses are increasingly attaching various AI agents to their existing systems including email and HR platforms or communications software like Slack.

Despite the benefits, there are concerns about giving novel technology complete access to internal systems. Archestra describes its service as the guardrails for AI data management.

“Model Context Protocal (MCP) is unlocking a new frontier for AI agents. But, right now, MCP is completely unsuitable for the enterprise,” said Archestra co-founder and chief executive Matvey Kukuy.

“We’re building the security-first solution that will change this. Our open-source platform means anyone, whether you’re an engineer or a HR rep, can safely and impactfully integrate AI agents into your workflow – driving efficiency and impact at scale – without increasing risks.”

The investment was led by Concept Ventures and featured participation from Zero Prime Ventures, Celero Ventures, RTP Global and Aloniq as well as a handful of angels.

“Just as APIs became the foundational building blocks for internet infrastructure, MCPs are emerging as the connective tissue for improving the context layer of AI tools within enterprise,” said Ariel Rahamim, principal at Concept Ventures

“Archestra is building the infrastructure layer this ecosystem needs. At Concept, we leaned into the teams’ technical depth, open-source DNA, and executional intensity to grow into a leader in the category.

“The team is attacking a mission-critical problem they’ve lived firsthand, and we’re confident they’ll define how enterprises deploy and govern AI context at scale.”

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