AI Governance

Take control of AI in your Enterprise. Ensure every AI interaction is policy-driven, auditable, and secure without slowing down innovation.

Govern AI usage across your organization before it governs you.

We’ve done it for us. Let’s do it for you. Schedule a free call with one of our AI Governance experts!

HOW WELL YOU GOVERN AI USAGE

AI adoption is accelerating faster than most organizations can control. Teams across the enterprise are already using cloud AI services from OpenAI, Anthropic, and Google. The question is no longer whether your people use AI, but how well you govern that usage.

Without a governance layer, AI interactions become invisible. Sensitive data flows into external models unmonitored, costs spiral unpredictably, and when auditors or regulators come asking, there are no trail logs to show. The EU AI Act is entering enforcement in August 2026, with requirements for risk management, human oversight, transparency, and comprehensive audit trails. Organizations that lack a structured governance approach face regulatory fines of up to EUR 35 million or 7% of worldwide turnover.

AI Governance is the answer. Not by restricting AI usage, but by building the infrastructure that makes AI usage visible, controlled, policy-driven, and auditable while keeping teams productive and innovative.

Schedule a free call with one of our AI Governance experts!

Find out how to take full control of enterprise AI with secure, compliant and fully governed usage without slowing down innovation.

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WHAT WE BRING TO THE TABLE

5 Pillars of AI Governance

Together, these five pillars form a complete governance layer that strengthens your AI landscape.

Policy & Access Management (AI Gateway)

Centralized policies that define who can use which AI models, for what purposes, with what budgets. Role-based access control ensures AI governance aligns with existing corporate identity and permission structures. A centralized control plane for all AI traffic. Every request to any cloud AI provider, OpenAI, Anthropic, Google, Mistral flows through a single, governed entry point with unified routing, access control, and usage tracking.

AI Guardrails

Automated safety enforcement at the point of every AI interaction. Input guardrails inspect every request before it reaches the AI model, detecting and redacting sensitive data (PII, credentials), blocking prompt injection attacks, and filtering prohibited content. Output guardrails then validate AI responses to prevent data leakage, enforce content policies, and ensure responses align with corporate standards.

Tracing & Observability

Full visibility into every AI conversation, decision, and action. End-to-end tracing captures what was asked, what internal data (documents, database retrievals, and API calls) was sent to the model, what was answered, and which model was used, creating the audit trail that compliance demands.

Regulatory Compliance & Audit Readiness

A governance foundation designed to meet the EU AI Act and other industry-specific regulations. Every AI interaction is logged, traceable, and ready for audit from day one.

Cost Control & Usage Analytics

Visibility into AI spend across teams, projects, and use cases. Budget limits, rate controls, and detailed usage analytics prevent runaway costs and provide leadership with clear insight into AI ROI.

1ST PILLAR

Policy & Access Management (AI Gateway)

A centralized control plane for all AI traffic. Every request, every response, every model interaction passes through a single governed layer before reaching external AI providers. Centralized governance policies that define the rules of AI engagement across the entire organization. Who can use what, under what conditions, with what constraints.

The LLM Gateway is the architectural backbone of AI Governance. It decouples applications and teams from direct AI provider integrations, creating a single enforcement point for policies, access control, logging, and routing. Whether an employee calls ChatGPT, Claude, Gemini, or Mistral, the request flows through the Gateway, making governance automatic rather than optional.

Unified API Layer: A single, provider-agnostic API interface for all cloud AI services. Applications integrate once and gain access to any model
Intelligent Routing: Route requests to the best-fit model with automatic failover and load balancing
Access Control: Enforce permissions at the gateway and determine which teams, services, or users can access which models and endpoints

Rate Limiting & Budgets: Enforce request limits and token budgets per team, per project, or per user to prevent abuse and manage costs
Virtual API Keys: Issue scoped API keys that map to internal teams and projects, eliminating the need to distribute provider credentials
Prompt Management: Centralized prompt governance to ensure consistent, high-quality interactions across the organization

2ND PILLAR

AI Guardrails

Automated safety enforcement on every AI interaction protecting sensitive data, blocking threats, and ensuring AI behavior aligns with corporate policies.

Guardrails operate at two critical points: before a request reaches the AI model (input guardrails) and after the response is returned (output guardrails). This dual-layer enforcement ensures that both prompts and completions are compliant, safe, and aligned with organizational standards. Guardrails are configured centrally and enforced consistently across all AI models and providers, without requiring application-level code changes.

PII Detection & Redaction: Automatically identify and mask personally identifiable information before it reaches external AI models, enforcing GDPR and data privacy requirements at the infrastructure level
Prompt Injection Prevention: Detect and block malicious prompt injection attempts that could manipulate AI behavior or extract system instructions

Content Policy Enforcement: Define allowed and disallowed topics, enforce brand guidelines, and prevent the generation of inappropriate, toxic, or off-brand content
Output Validation: Scan AI responses for hallucinated data, sensitive information leakage, or content that violates compliance rules before it reaches end users
Multi-Level Configuration: Apply guardrails globally across the organization, enabling flexible governance that scales with organizational complexity

3RD PILLAR

Tracing & Observability

Full end-to-end visibility into every AI interaction across the organization. From the initial user prompt through model inference to the final response.

Tracing transforms AI usage from a black box into a transparent, auditable system. Every conversation, every API call, every tool invocation is captured with complete context: who asked, what was asked, which model responded, how long it took, what it cost, and what the response contained. This creates the comprehensive audit trail that regulators require and that operations teams need for debugging, optimization, and quality assurance.

Request-Level Tracing: Capture the full lifecycle of every AI interaction: input prompt, model parameters, output response, token usage, and latency.
Multi-Step Pipeline Tracing: Follow complex AI workflows across multiple model calls, tool invocations, and processing steps, understanding exactly how a result was produced

Audit Trail Generation: Immutable, timestamped records of every AI interaction
Cost Analytics: Granular cost tracking per model, per team, per project

4TH PILLAR

Regulatory Compliance & Audit Readiness

A governance architecture built from the ground up to meet current and upcoming regulatory requirements like the EU AI Act.

The EU AI Act, entering full enforcement for high-risk AI systems in August 2026, requires organizations to implement risk management systems, maintain detailed technical documentation, ensure human oversight, and demonstrate transparency. Beyond the AI Act, GDPR restricts automated decisions with legal effects and demands data protection safeguards, while NIS2 and DORA impose additional cybersecurity and operational resilience obligations. The AI Governance platform provides the technical foundation to meet these requirements systematically rather than retroactively.

5TH PILLAR

Cost Control & Usage Analytics

Clear visibility and control over AI spend across the entire organization transforming unpredictable token-based costs into a manageable, optimized expense.

Cloud AI services are priced per token, which scales rapidly as adoption spreads across teams and departments. Without centralized visibility, AI costs can grow exponentially and unpredictably. The AI Governance platform provides real-time cost tracking, budget enforcement, and optimization insights that keep AI spend aligned with business value.

Real-Time Cost Tracking: Monitor AI spend in real-time across providers, models, teams, and projects
Budget Enforcement: Set hard or soft spending limits per team, project, or use case

Model Optimization Insights: Identify opportunities to route requests to more cost-effective models
Trend Analysis: Track usage patterns over time to forecast future AI spend, identify seasonal peaks, and plan capacity accordingly

Our approach

4-step AI Governance Framework

We follow a structured four-step approach to deliver comprehensive AI Governance.

1.

Analysis

We assess your current state by evaluating existing infrastructure, AI use cases, security requirements, and organizational readiness. This step identifies gaps between where you are today and where you need to be for governed AI at scale.

2.

Proposal AI Governance Design

Based on the analysis, we produce a tailored solution architecture. This includes evaluating components across AI Gateway, Observability, Guardrails, and Governance dimensions, presenting a shortlist of solution options with clear trade-offs for your decision. We always take into account existing IT infrastructure components and potential reuse of existing components.

3.

PoC for Verification

We deploy a proof of concept of the selected architecture, validating it against defined acceptance criteria. The PoC tests functional completeness, observability coverage, performance, and security posture with a controlled user group before broader rollout.

4.

Rollout

Based on PoC learnings, we plan and execute organization-wide deployment. This includes phased user onboarding, operational runbooks, knowledge transfer, and an ongoing support model for sustainable governance operations.

WHAT WE BRING TO THE TABLE

Why Work With Us?

PROVEN EXPERTISE

Proven expertise in building enterprise AI platforms, including LLM Gateway deployment, guardrail systems, tracing infrastructure, and identity integration, built on real-world experience with production AI systems at scale.

DEEP UNDERSTANDING

Deep understanding of regulatory requirements, with practical experience implementing compliance frameworks across multiple industries.

TECHNOLOGY AGNOSTIC

Technology partners include NVIDIA, IBM, Red Hat, Mistral, and ClearML, ensuring access to enterprise-grade tooling and support.

INTERNAL ENTERPRISE AI PLATFORM

Our capabilities are anchored by our internal Enterprise AI Platform, which serves as a living reference implementation demonstrating governance, traceability, and operational maturity in a production environment.

CONTACT

If you have any questions, we are one click away.