001 — ENTERPRISE AI INFRASTRUCTURE

OperationalIntelligence

We design, deploy, and govern production-grade AI systems for organizations where intelligence must behave like critical infrastructure.

Deployment
Cloud / On-Prem / Hybrid
Governance
Full Audit Trail
Models
Vendor Agnostic
Base
European
002 — PLATFORM

Two Systems.
One Architecture.

A layered architecture where Atlas provides the intelligence substrate and Forge delivers the control plane. Together, they transform AI from experimental capability into reliable enterprise software.

A

Atlas

Intelligence Platform

The enterprise AI platform connecting data estates to agentic reasoning and reliable action. Governed knowledge retrieval, policy-driven model routing, and complex workflow orchestration with full auditability.

01
Knowledge Layer
Governed retrieval across enterprise data
02
LLM Gateway
Policy-driven routing, cost control, no shadow AI
03
Agent Runtime
Orchestration with lifecycle management
04
Automation
Long-lived, auditable workflow execution
F

Forge

Control Plane

The enterprise control plane for deployment, versioning, compliance, and observability. Forge ensures AI systems remain secure, performant, and cost-efficient throughout their operational lifecycle.

01
Deployment
Automated versioning and rollout orchestration
02
Compliance
Policy hooks, access control, audit trails
03
Observability
Real-time monitoring and alerting
04
Economics
Cost governance and usage analytics
003 — SERVICES

Engineering
Partnership

Forward-deployed engineering that bridges ambiguous business problems and durable software. Not consultants with frameworks—engineers who ship production systems.

Primary Engagement

Forward-Deployed Engineers

Senior engineers embed with your teams to design architecture, deliver initial use cases, and harden systems for production. They write code. They own outcomes.

Architecture Design
Use Case Delivery
Production Hardening
Knowledge Transfer
Ongoing Support

Managed Operations

Operational stewardship that evolves with your usage. Model updates, policy tuning, performance optimization, and compliance maintenance as your AI systems mature.

Model Updates
Policy Tuning
Performance Optimization
Compliance Maintenance
Models alone do not create durable advantage. Integration, governance, and execution do.
004 — METHODOLOGY

Principles of
Enterprise AI

We operate where critical software meets organizational reality—integrating with systems of record, enforcing policy, and ensuring AI behaves predictably under production constraints.

I

AI-First

Systems designed around reasoning and automation from the outset. Not AI bolted onto legacy architecture.

II

Enterprise-Ready

RBAC, compliance hooks, audit logs, observability, and cost governance are foundational—not afterthoughts.

III

Beyond Chat

Agentic behavior, tool use, planning, and policy-as-code. AI as an execution system, not merely an interface.

IV

Integration-First

AI derives value only when connected to enterprise data and workflows. Isolation is failure.

Platform Architecture

Modular infrastructure enabling cloud, on-prem, or hybrid deployment with full vendor abstraction and eject optionality.

05Automation Runtime
04Agent Runtime
03LLM Gateway
02Data Foundation
01Platform Foundation
005 — CONTACT

Ready to
Operationalize?

We work with organizations moving from AI experimentation to production-grade systems. If that describes your trajectory, let's discuss.

contact@klyon.de
Ideal Engagement Profile
01Large enterprises with complex system landscapes
02Organizations transitioning from pilot to production
03Environments requiring governance, traceability, and compliance
04Teams building durable automation over point solutions