Alltegrio Launches Private LLM Solution for Secure Enterprise AI

New on-premise and private cloud LLM infrastructure helps enterprises maintain data residency, strengthen compliance, and deploy AI without exposing sensitive information.

Alltegrio today announced the release of its private LLM & data residency solution, a new enterprise on-premise AI infrastructure offering built for organizations that cannot risk exposing sensitive data to third-party model providers. By supporting fully private deployment models, including on-premise AI and VPC environments, the service helps enterprises meet regulatory demands while moving forward with AI in a more controlled and secure way.

The growing challenge of secure AI adoption

The security and compliance gap in public LLM usage
As enterprises expand their use of Large Language Models, many are running into a familiar issue: the tools are powerful, but the deployment model introduces risk.

Most LLM implementations rely on external APIs, which means data is processed outside the organization's own infrastructure. That immediately limits visibility and raises questions around storage, access, and long-term usage of that data.

In environments governed by GDPR or HIPAA, limited control over data handling can become a real issue. Organizations can't rely on assumptions-they need to see how data is handled and have the tools to monitor and audit it when needed.

In practice, this is where many AI initiatives slow down. Not because the technology isn't useful, but because the way it's typically deployed doesn't meet the standards for enterprise AI security and compliance.

Bringing LLM infrastructure inside the enterprise

For organizations facing these challenges, the solution isn't just better security-it's a different way of deploying AI altogether.

Alltegrio's private LLM & data residency service (https://alltegrio.com/) is built around the idea that AI should operate inside your environment, not outside of it. Instead of sending data to external APIs, models are deployed directly within on-premise systems or private cloud environments.

This changes how data is handled at every step. Information stays within internal infrastructure, and processing happens in controlled, isolated environments. There's no need to route sensitive data through third-party services, which removes a major source of uncertainty.

At the same time, secure pipelines control how data moves between systems, making each step visible and easy to track.

This keeps everything aligned with internal policies and ensures the AI setup works with existing workflows and governance, rather than forcing teams to adapt around it.

"AI adoption shouldn't come at the cost of data control," said Oleg Goncharenko, the CEO of Alltegrio. "For many enterprises, that's been the trade-off with public LLMs. Our goal is to remove that compromise entirely-bringing AI closer to where the data already lives, so organizations can move forward with confidence, not hesitation."

Enterprise-grade capabilities for secure AI deployment
Flexible deployment across environments

The solution can run either on-premise or in a private cloud environment like AWS, Azure, or GCP VPCs, making it easier for organizations to fit AI into their existing setup and data requirements.

Custom models trained on internal data

Organizations can adapt Large Language Models using their own data, so outputs better reflect their processes, terminology, and domain expertise.

Secure inference and data handling

Every interaction with the model runs through secure pipelines, so inputs and outputs stay within controlled systems. This reduces exposure risk and keeps sensitive data handling consistent.

Access control, monitoring, and auditability

The platform includes role-based access control, along with logging and monitoring, so teams can manage access, monitor usage, and stay informed across AI activity. It connects with existing enterprise systems, helping AI fit into how teams already work.

Built to work within existing systems

The solution connects AI directly to internal systems such as CRMs, ERPs, data warehouses, and workflow tools, allowing it to operate within real processes and support actions across systems-not just generate responses.

Data residency and compliance by design

The Private LLM solution helps organizations meet data residency and compliance requirements while keeping full control over how their data is handled across AI systems.

● Data stays within defined environments. All data processing is limited to controlled on-premise and private cloud environments, ensuring it remains within defined boundaries.

● Support for key regulatory frameworks. The solution supports compliance with GDPR, HIPAA, and SOC 2, helping organizations meet regulatory requirements for secure AI deployment.

● Full control over data location and movement. Organizations decide where their data lives and how it's processed, making it easier to meet data sovereignty and localization requirements.

● Built-in governance and visibility. Teams have clear insight into data flows, access, and system activity, making it easier to enforce internal governance policies.

What this means for enterprise AI adoption

For many organizations, the main barrier to AI adoption isn't the technology-it's the risk around data, compliance, and control. A private LLM approach helps remove that barrier.

● Keep full control over data. Data stays within internal systems, reducing uncertainty around how it's handled.

● Lower compliance risk. Easier alignment with regulatory requirements when data remains in controlled environments.

● Build internal trust in AI systems. Teams are more comfortable using AI when they understand how it works and where data goes.

● Enable AI in sensitive environments. Makes adoption possible in industries with strict enterprise AI security and governance requirements.

● More predictable costs. No dependency on external APIs means fewer surprises in usage-based pricing.

Practical applications for private LLM deployment

The solution enables AI adoption across use cases where security, compliance, and data control are essential.

● Internal knowledge assistants for secure access to internal data

● Legal document analysis within controlled environments

● Healthcare data processing aligned with compliance requirements

● Financial risk analysis without external data exposure

● Enterprise copilots operating within internal systems

Learn more about private LLM deployment

Organizations interested in deploying private LLM infrastructure can request a demo or connect with Alltegrio's team to explore how the solution fits their environment and requirements.

About Alltegrio

Alltegrio is a provider of enterprise AI and data solutions, specializing in Large Language Models and AI agent-based systems. The company delivers end-to-end development and deployment of AI infrastructure designed for secure, compliant, and scalable use across enterprise environments.

This release was published on openPR.