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By Matthias Gysi, Presales Engineer, Squirro

Squirro: The AI platform for regulated industries

At first glance, AI looks easy. Type a prompt into a browser, and you immediately get an answer. But when you transfer it to the enterprise, you quickly realize that it isn't that simple. So why are so many businesses hitting a wall as they try to scale experimental PoCs to production? Because most enterprise AI stacks fail to achieve the accuracy, security, and compliance required in real-world, high-stakes deployments.

The Squirro platform provides a secure foundation for generative AI. It lets organizations safely delegate everyday knowledge work, such as writing on-brand content, summarizing dense legal documents, or comparing complex compliance data, while mitigating hallucinations through strict factual grounding. By transforming their disparate data sources into a single source of truth, Squirro helps teams uncover hidden insights and agentically automate entire enterprise workflows, transforming AI into a core business utility that meets the demands of highly regulated industries.

Countering shadow IT with enhanced RAG

By now, we've all seen the value of GenAI in terms of efficiency gains. That's why it's hard to blame those that want to use the technology in their daily activities. But when employees share work-related data with non-approved AI services, so-called shadow IT, they expand the digital attack surface and introduce massive security risks. Data breaches, compliance failures, and the exposure of proprietary IP to third-party model trainers are real threats that can cause lasting reputational damage.

The Squirro enterprise AI platform was built specifically to give organizations a secure, accurate, and permissions-enabled way to integrate GenAI into their operations. Because it uses retrieval augmented generation (RAG) to augment user prompts with data stored in an organization's enterprise platforms, its performance is far beyond what an off-the-shelf large language model can deliver.

But while standard RAG retrieves data from internal and external sources to ground an LLM's outputs, Squirro's enhanced retrieval augmented generation (RAG) stack goes several steps further to enhance accuracy and protect customer data:

• Knowledge Graphs provide deeper deterministic grounding to ensure the AI understands relationships between entities, not just word frequencies.
• Data Virtualization enables real-time integration without needing to constantly ingest fast-changing datasets.
• AI Guardrails ensure that GenAI outputs consistently adhere to corporate policy and regulatory requirements.
• The Privacy Layer automatically masks and scrubs personally identifiable information (PII) before it ever reaches the LLM, enabling the use of state of the art LLMs from US based hosting providers without GDPR violation.
• The Agentic Framework helps users move beyond simple task acceleration to end-to-end workflow execution drawing on your proprietary data.

This provides a compliant alternative to shadow IT, allowing users to leverage generative AI within a secure enterprise framework.

Controlling your destiny with full data sovereignty

Ask business leaders in the DACH region what is holding back AI adoption in their organization, and you'll likely hear a common response: legal anxiety surrounding data privacy. And it goes beyond standard security vulnerabilities. The U.S. Cloud Act, enacted in 2018, creates a jurisdictional gray area by allowing US authorities to request data from any cloud service providers headquartered within its borders, regardless of where that data is physically stored. For the public sector, healthcare, and banking, this isn't just a compliance hurdle, it's a question of data ownership.

Squirro delivers total data sovereignty by giving organizations absolute control over where their data resides. Whether deployed in a Virtual Private Cloud (VPC) or fully on-premises, Squirro ensures sensitive information never leaves your perimeter. Pairing Squirro with cloudscale allows Swiss organizations to scale their AI operations without relying on providers subject to the U.S. Cloud Act.

Scalable data access control management

One of the most overlooked hurdles in Enterprise AI is permissions. If you build a GenAI application that taps into all your corporate data, how do you ensure that a junior analyst doesn't accidentally gain access to the CEO's salary or a confidential M&A memo?

Managing access control lists (ACLs) becomes increasingly complex as organizations scale. Squirro handles this by assigning access-control metadata to each document chunk at the moment of ingestion. Permissions are embedded into the retrievable unit itself. When a user asks a question, the similarity search only returns authorized chunks. If you don't have permission to see the document, the LLM doesn't even know the document exists, preventing unauthorized exposure to third parties.

We have proven this at scale, managing over 10 TB of index data with over 10,000 user groups for a major central bank, proving that security doesn't have to sacrifice performance.

Future-proofing your AI strategy

Combining Squirro and cloudscale provides a turnkey sovereign enterprise AI platform that operates independently of major U.S. hyperscalers. This isn't just about deploying an industry-hardened technology stack; it's about removing the legal and security friction that stalls AI projects in the boardroom.

Ultimately, the choice between AI adoption and sovereignty is a false one. You don't have to trade your data privacy for a productivity boost. By deploying Squirro on cloudscale, you can cut the time it takes to adopt sovereign Enterprise AI, building on a foundation that you, and only you, own.

We've successfully installed Squirro on cloudscale to verify the integration; if you'd like to see how it looks or try a test instance, please get in touch with the Squirro Sales Team.