Cortif AI and Onepoint: Building the Infrastructure Layer for Enterprise AI

Artificial intelligence is rapidly moving from experimentation to mission-critical enterprise infrastructure. As organizations deploy large language models (LLMs) into production applications, they face new challenges: managing inference costs, enforcing security policies, ensuring compliance, and maintaining reliability at scale.

This is where Cortif AI and Onepoint are collaborating.

Through an early design partnership, Onepoint is exploring the integration of Noah, Cortif's AI infrastructure platform, into its enterprise AI ecosystem, including its Neo chatbot platform used by enterprise customers.

The goal: bring monitoring, governance, anomalies prediction, security and cost optimization to enterprise AI systems.

About Onepoint: A Major European Digital Transformation Firm

Founded in Paris, Onepoint is one of France's leading consulting and technology firms focused on digital transformation. The company employs more than 4,000 professionals across multiple countries and generates over €500 million in annual revenue, serving large enterprises and public institutions worldwide.

With offices across Europe, North America, and Asia-Pacific, Onepoint helps organizations design and implement large-scale technology systems spanning data, AI, cloud infrastructure, and digital transformation programs.

Its clients include major companies across sectors such as finance, telecommunications, public sector, transportation, and industry.

As enterprises increasingly adopt generative AI, Onepoint is expanding its capabilities to support organizations in building, governing, and scaling AI systems responsibly.

This is where the collaboration with Cortif AI begins.

Why Enterprise AI Needs Infrastructure

While large language models have unlocked powerful new capabilities, operating them in production is complex.

Companies deploying AI systems often encounter problems such as:

• Unpredictable inference costs
• Limited visibility into model behavior
• Security risks from prompt injection or unsafe agents
• Difficulty maintaining performance across models
• Lack of governance or policy enforcement

Many organizations start with simple API integrations but quickly realize that AI systems require an operational layer similar to what cloud infrastructure provides for traditional software.

Cortif AI was built to provide exactly that.

Introducing Noah: The AI Control Plane

At the center of Cortif's technology stack is Noah, an enterprise platform designed to act as the control plane for AI systems.

Noah sits directly in the inference pipeline between applications and AI models, providing the infrastructure necessary to monitor, secure, and optimize AI workloads in real time.

For Onepoint, Noah presents a powerful layer that can be integrated into enterprise AI deployments, including the Neo chatbot platform, which serves multiple enterprise customers.

Through this integration, organizations can gain greater control over how their AI systems operate in production environments.

The LLM Gateway: A Unified Entry Point for AI Systems

One of Noah's core components is its LLM Gateway, which acts as a centralized routing layer for all AI model requests.

Instead of directly calling a specific model provider, applications send requests through Noah's gateway, which enables:

• centralized AI traffic management
• model routing across providers
• token usage tracking
• latency monitoring
• real-time observability

This architecture provides organizations with complete visibility into their AI infrastructure while enabling dynamic optimization of requests.

For enterprises deploying AI at scale, this level of observability becomes critical.

Intelligent Model Rerouting and Cost Optimization

One of the biggest challenges in production AI systems is controlling inference costs.

Different models have different performance profiles and pricing structures, and many organizations unknowingly overspend on expensive models for tasks that could be handled by smaller ones.

Noah addresses this through an intelligent LLM rerouting system.

Requests can be dynamically routed to the most efficient model depending on:

• task complexity
• latency requirements
• cost constraints
• system availability

Combined with prompt optimization techniques, this system can significantly reduce the overall cost of operating AI systems without sacrificing performance.

Securing AI Agents with the Policy Enforcement Gateway (PEG)

As AI agents become more autonomous, security and governance become even more important.

To address this challenge, Cortif recently introduced the Policy Enforcement Gateway (PEG).

PEG acts as a real-time interception layer between users and AI agents.

Before any prompt is forwarded to an agent, PEG evaluates the request against the organization's policy rules.

The process works as follows:

1. A user or application sends a prompt to an AI agent
2. PEG intercepts the request before it reaches the agent
3. The prompt is evaluated against a company's policy bundle
4. If the request violates policy, the system blocks it and returns a structured rejection
5. If the request passes validation, it is forwarded to the agent transparently

This architecture enables organizations to enforce governance policies in real time, protecting AI systems from misuse, prompt injection, or unsafe behavior.

Monitoring Model Drift and System Reliability

AI systems evolve over time, and their behavior can change as inputs and usage patterns shift.

Noah includes model drift detection, robustness testing, and forecasting capabilities that allow organizations to monitor the health of their AI systems continuously.

These tools help teams:

• detect performance degradation early
• evaluate model robustness under changing conditions
• forecast system behavior as workloads grow

For enterprises deploying AI at scale, this layer of monitoring ensures long-term reliability and stability.

Enabling AI Compliance and Governance

In addition to technical infrastructure, Onepoint is developing an AI compliance and governance offering for its enterprise clients.

As global regulations such as the EU AI Act begin to shape how AI systems must be deployed and monitored, organizations need tools that ensure responsible and auditable AI operations.

Noah's infrastructure, including observability, routing controls, and policy enforcement, provides a foundational layer that supports these compliance efforts.

By combining Onepoint's consulting expertise with Cortif's AI infrastructure technology, the partnership aims to deliver a comprehensive approach to enterprise AI governance.

The Future of Production AI Systems

AI is quickly becoming a core layer of modern digital infrastructure.

However, just as cloud computing required platforms like Kubernetes and observability stacks, AI systems require their own operational infrastructure.

The collaboration between Cortif AI and Onepoint reflects a growing realization across the industry:

the next phase of AI will be defined not just by models, but by the infrastructure that allows them to run safely, efficiently, and reliably.

Through the integration of Noah into enterprise AI ecosystems, both organizations are helping build the operational foundation for the next generation of AI-powered systems.