Who Architects the Operations?
European enterprises need agent infrastructure that is governed, reliable, and compliant. We build it.
Your AI Strategy Is a Deck. Your Operations Are Still Manual.
Every enterprise is piloting agents. Almost none have the architecture to run them. The problem is not the technology. The problem is the operating layer.
Agents Piloted, Not Governed
Teams bolt agents onto existing workflows. A chatbot here. An automation there. Each one works in isolation. None of them talk to each other.
No Governance Framework
Nobody has defined what agents can do autonomously and what requires a human decision. The EU AI Act requires this. Most companies have not started.
51% Piloting, 0% Operating
Experiments and operations are different things. Most enterprise AI initiatives produce demos, not systems that run without daily intervention.
ROI Unclear After POC
Proof-of-concept succeeds. Budget is approved. Then the real question: who architects the production system? The POC team has moved on.
Security and Compliance Exposure
Every unarchitected agent is a compliance risk. Data flowing through unmonitored prompts. No audit trail. No access controls. No observability.
Talent Gap: Who Runs This?
The role of 'agent operations architect' barely exists. Companies need the capability now. Hiring takes 6 to 18 months. The gap is widening.
“51% of enterprises are piloting agents. Most have no plan for operating them.”
-- Capgemini Research Institute, 2026We Build the Operating Layer.
Verluna architects agent systems the way infrastructure engineers architect cloud deployments. Not one tool at a time. The entire operating layer.
Routing & Specialization
Every piece of incoming work goes to the right agent, the right process, the right human. No manual triage. Dedicated agents per domain instead of one general-purpose system that does everything poorly.
A field marketing team had one person manually routing event leads, enriching data, and matching accounts. We decomposed this into three bounded agents -- each with a clear mandate, clear boundaries, and clear escalation paths.
Governance & Compliance
Explicit rules for what runs autonomously, what requires human approval, and how the system behaves when something unexpected happens. Built for the EU AI Act from day one, not retrofitted.
An autonomy classification system with three tiers: autonomous (lead routing, data enrichment), supervised (scoring adjustments, content generation), and human-only (budget decisions, strategic pivots). Every agent knows its tier.
Memory & Observability
Persistent context that survives across sessions, across agents, across teams. You can see what every agent did, why it did it, what it cost, and whether it worked. No black boxes.
An operating system with persistent memory across 7 domains, event-driven hooks that auto-sync state, and cadence scheduling that ensures morning briefs, weekly reviews, and monthly reports happen without manual triggers.
Six Phases. One Operating Layer.
Emerged from 300+ production AI sessions, enterprise deployments, and the experience of redesigning real operations as AI-native systems. Not a theory. How we work on every engagement.
Phase 01: Observe the Operation
Never start by building. Start by watching how things actually work. Not how the org chart says they work. Not how the process document describes them. How people actually spend their time, where information breaks, and where humans do work that machines should handle.
Watched a field marketer spend 4 hours doing XLOOKUP to match event attendees against target accounts. The observation: fuzzy matching with German company name variants (GmbH, AG, spelling variants) was the actual bottleneck.
4 hours to 90 seconds.Deliverables
- +Process observation report
- +Information flow map
- +Decision-point inventory
- +Bottleneck identification
Tools & Methods
- $Stakeholder interviews
- $Process shadowing
- $Data flow analysis
Four Ways to Work With Us. Start Where You Are.
Every engagement follows the same six-phase methodology. The scope depends on where you are.
Agent Readiness Audit
- +Architecture diagram of your entire GTM stack with data flows and integration gaps
- +Automation maturity score benchmarked against 50+ B2B SaaS operations
- +Prioritized roadmap with estimated ROI for each opportunity
- +30 days of post-launch support included
Agent Architecture Build
- +Autonomous workflows that handle repetitive operations your team does by hand
- +Agent-powered processes designed with the autonomy gradient
- +Documentation and training so your team owns the system after we leave
- +Production deployment, not a prototype engagement
Managed Agent Operations
- +Two-week experiment sprints that test, tune, and ship improvements
- +Monthly performance reports with metrics that matter
- +One architect with an agent workforce: throughput of a 3-to-5-person team
- +Scale operations without scaling payroll
Agent Architecture Consulting
- +Domain decomposition of your operations into bounded areas with clear ownership
- +Governance framework defining autonomous vs. human-approved actions
- +Agent infrastructure blueprint: orchestration, memory, security, observability
- +Vendor-neutral, based on production patterns
Not sure where to start? 80% of clients begin with the audit.
Built for European Enterprises.
EU AI Act ReadyUS-based AI consultancies optimize for speed. European enterprises need architecture that is governed, compliant, and auditable from day one. That requires a partner who builds governance into the foundation, not as a compliance layer bolted on after launch.
Verluna is that partner. Berlin-based, DACH-fluent, and purpose-built for the regulatory and operational reality of European B2B.
EU AI Act Compliance by Design
Agent governance frameworks built from Article 9 risk assessment requirements. Autonomy classification, human oversight mechanisms, and audit trails are architectural decisions, not afterthoughts. We design for the regulation that takes effect in 2026.
GDPR-Native Data Architecture
Data residency, consent management, and processing agreements are part of the infrastructure blueprint. Agent memory systems designed with data minimization and purpose limitation built into the architecture. No cross-border data flows without explicit design.
Berlin-Based, DACH-Fluent
We operate in your timezone, understand your market dynamics, and work in German when needed. DACH B2B SaaS is not Silicon Valley. Company name matching with GmbH, AG, and SE variants. HubSpot configurations for European field marketing workflows.
Data Sovereignty First
European enterprises cannot afford agent systems that route data through US infrastructure without controls. We architect for EU data residency, design with European cloud providers as first-class options, and ensure your agent infrastructure respects the boundaries your compliance team requires.
Built in Production, Not in PowerPoint.
“4 hours of manual matching reduced to under 2 minutes.”
Semantic matching system -- B2B SaaS“7 research sessions produced a complete attribution architecture at zero software cost.”
Marketing intelligence -- Enterprise“10 reference documents synthesized from a complex enterprise codebase.”
Knowledge codification -- Enterprise“We build working systems, not strategy decks.”-- Verluna
How It Works in Practice.
4 hours of manual matching became 90 seconds of semantic AI.
A global language technology company's field marketing team was spending 4 hours per event matching attendee lists against target accounts using XLOOKUP with German company name variants. Verluna built a semantic matching system that handles fuzzy matching across GmbH, AG, and spelling variants.
Designing a multi-touch attribution architecture with agent-powered research. Zero external software.
7 research sessions produced a complete attribution architecture. Three independent scoring domains (Fit, Engagement, Product), each with its own data sources and models. Built entirely on existing CRM infrastructure.
7,179 lines of enterprise documentation synthesized into 10 operational reference files.
A complex enterprise codebase decomposed into 10 bounded domains. Each file self-contained. A decision tree at the top routes readers to the right domain. Used daily by the operations team.
How Ready Is Your Organization for Agent Operations?
Take the Verluna Agent Operations Scorecard. 12 questions. 5 minutes. You get a benchmark score across four dimensions: Agent Governance, Infrastructure Readiness, Team & Skills, and Compliance & Security.
Plus a one-page recommendation on where to start.
No sales call required. No email sequence. Just the score and the recommendation.
Take the Free Assessment (5 minutes)The Agent Operations Briefing.
Why the Operating Layer Is the Most Valuable Thing to Build Right Now
Every company is buying AI tools. Almost none are designing the infrastructure between those tools and their business processes. That gap is where value lives.
Read articleEU AI Act Compliance for Agent Systems: What Your Engineering Team Needs to Know
Article 9 risk assessments, human oversight requirements, and audit trail obligations. A practical guide for companies deploying autonomous agents in Europe.
Read articleFrom Observation to Autonomy: How We Turn Manual Operations into Agent-Powered Systems
A detailed walkthrough of the six-phase methodology using a real engagement. From watching someone do XLOOKUP to shipping a production Kubernetes deployment.
Read articleThe Agent Operations Briefing
Every two weeks: one actionable insight on AI agent infrastructure, governance patterns, and European compliance.
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Built by a Practitioner, Not a Consultant.
Verluna was founded by Tolga Oral, a marketing operations leader who spent a decade building automations for B2B SaaS companies across DACH. Not a developer by training, but someone who shipped production AI systems across 300+ sessions because real operational problems demanded real systems.
The origin story is simple: a marketing ops person who kept hitting the limits of configuration. HubSpot workflows that couldn't handle the logic. Spreadsheets that broke when the data scaled. Vendors who promised integration but delivered manual steps.
Then AI coding tools changed what one person could build. Not “no-code” -- actual code. Production systems. Deployed on Kubernetes. Used by real employees. The discovery: the operating layer between AI and business is the most valuable thing to build right now, and European enterprises need someone who understands both sides.
That thesis became Verluna.
- +300+ AI production sessions with enterprise systems
- +10 years of marketing operations in DACH B2B SaaS
- +Production systems deployed on Kubernetes for enterprise users
- +HubSpot, Salesforce, and n8n automation architecture
>prompt Developer Conference
April 2026 -- “AI Coding as a Non-Developer: Building Production Systems with Claude Code”
Berlin, Germany
Working with clients across DACH and the EU
Stop Piloting. Start Operating.
The window between “experimenting with AI” and “losing ground to companies that operationalized it” is closing. Verluna helps European B2B companies cross that gap with architecture, not experiments.
30 minutes. No pitch. We map your agent readiness and tell you the 3 highest-impact moves.