Working AI Agents
Delivered for Kärcher
We build AI agents that automate your highest-volume workflows. Predictable outputs. Measurable cost savings. Owned by Kärcher.
Romania-led pilot. Portable blueprint for Winnenden-led global rollout.
Who's behind this
Industrial operators
who happen to do AI.
The team has delivered inside Siemens (internal change agent during the Siemens Nixdorf merger — McKinsey-selected), GEC (industrial transformation across manufacturing, service, distribution), IBM, Sun Microsystems, Emerson (SCADA patent), Lloyds Banking Group. Before we talk AI, we've spent decades inside large industrial and enterprise environments — manufacturing, factory operations, service, and sales. We speak Kärcher's language first, AI second.
What Phase 1 Fixes
The blockers that prevent AI
from becoming an operating capability.
Service Productivity & Spare Parts Execution
Group-wide Gemini Rollout — Ready for a Governance Baseline
Multiple AI Platforms — an Opportunity for Group MIS Coherence
Connected Fleet: Service Intelligence Potential
KIRA Robotics: From Strong Product to Fleet-wide Intelligence
Cost-to-Serve: the Lever Behind Record Revenue
Regulatory
EU AI Act high-risk obligations come into force August 2026. Kärcher's Group-wide Gemini rollout, the KIRA autonomous fleet, and the multi-vendor AI estate all need a governance layer before the deadline.
Commercial
Record revenue with a material growth slowdown vs prior years. Classic trigger for family-owned German boards to push efficiency, reskilling, and cost-to-serve reduction — without touching employment. Phase 1 puts evidence behind that answer.
A Phase 1 pilot started this quarter gives Winnenden a defensible answer on both — not a scramble.
Seen enough? Start with €30K-€50K.
30-minute scoping call. Small enough to start before a full committee review.
What We Offer
We deliver working AI.
You own the agents. You keep the savings.
Tier-1 consultancies deliver slide decks and renewal contracts. We deliver working AI agents on your real workflows — inside your environment, behind your firewall. Every agent Kärcher owns from day one. No SaaS, no PaaS, no long-term proprietary tie.
The core principle
The agents handle the volume. Your people handle what requires judgment.
These AI agents are not here to replace Kärcher employees. They drive cost saving and revenue generation by automating high-volume, repetitive work with predictable, auditable outputs — so your team spends their time on decisions, innovation, and complex engineering.
Fix
We identify and stabilise the operational blockers preventing AI from becoming an owned operating capability. Real workflows, real systems, real evidence.
Build
We deliver working AI agents on your highest-pain workflows. Customer relations triage. Service diagnostics. Procurement automation. Predictable outputs that drive cost savings.
Prove
Every agent ships with measured results. Handle-time reduction, cost-per-resolution, accuracy rates. Evidence your leadership can use — internally and upward to Group.
The Value for Kärcher
What this fixes.
Specifically. For you.
You already know which workflows are painful. Phase 1 picks three or four and proves them.
Sponsor-led selection from a menu: Jira-integrated service triage and spare-parts workflow automation, customer self-service for maintenance and parts (direct Siemens precedent from Mru Patel), fleet predictive maintenance, service diagnostics assistant, cross-country commercial productivity (sales standardisation, pricing discipline), supply chain forecasting, procurement automation, internal knowledge management. Whatever Kärcher picks becomes the evidence base for Phase 2.
Revenue is high but growth is decelerating. Operational efficiency is the next lever.
Kärcher posted a record €3.48B, but growth has materially slowed vs prior years — the classic trigger for German family-owned boards to push efficiency, reskilling, and cost-to-serve reduction without threatening employment. Phase 1 produces 3-4 working agents and a blueprint that turns manual processes into automated output. Margin improvement the board can defend.
Group-wide Gemini usage + a governance baseline.
12 trained staff who speak the same AI architecture language. A governance baseline that coordinates what's already happening internally with Gemini, SAP AI, robotics, and procurement tooling — reducing long-term consultant dependency and making local teams faster without growing headcount.
Your AI stack already belongs to four different vendors.
Every agent your team builds belongs to Kärcher. The architecture blueprint lives on InfoAcademy. Zero APEX dependency after Phase 1 if you choose not to continue. The unifying layer that makes your existing AI investments work together.
Track Record
We already built this.
For ourselves and for clients.
GTM Agentic Platform
Co-Founder, Cognition Architecture
Co-founding a plug-and-play GTM platform (€33B TAM) with an established EU procurement founder. Enterprises connect their vendor and customer data. The cognition layer handles discovery, qualification, matching, and onboarding autonomously. Full vendor lifecycle outsourced to AI, not to a consulting firm. Built on €3M+ of existing R&D.
In DevelopmentYour Team
Enterprise engineering.
AI-native delivery.
IBM, Sun Microsystems, and Lloyds pedigree. 60+ years enterprise delivery. Cloud, security, and SCADA engineering. Delivered through InfoAcademy.
Strategic Leadership
Nico Fratila
Founder & CEO of APEX OS, the sovereign AI operating system running 24/7 on Azure with 400+ self-evolving skills, persistent agent memory, multi-model orchestration, self-healing infrastructure, and a knowledge distillation engine. Also runs InfoAcademy, an enterprise AI training platform. Background spans 5 years of network engineering at Lloyds Banking Group (cloud migrations and operational transformation), business analysis and project & programme management across FinTech and RegTech, and scalable platforms built from scratch. Chief Customer Office at CUBE Global. Helps founders and businesses move from concept to execution with battle-tested frameworks, AI automation, and hands-on technical expertise.
Mru Patel
40 years at the intersection of enterprise technology and commercial strategy inside large industrial companies. Direct Kärcher-relevant pedigree: internal change agent at Siemens during the Siemens Nixdorf merger, selected by McKinsey for the innovation programme — first-hand experience of how large German industrial groups actually buy, adopt, and govern technology. Industrial-transformation work across GEC (General Electric Company plc, UK) covering manufacturing, service, and distribution. Architected a customer self-service transformation at Siemens (agents + instructional content) that increased loyalty and cut service overhead — a direct precedent for what Kärcher could do with maintenance, parts, and diagnostics. Led multi-billion-pound programmes at IBM, Siemens, GEC, and Sun Microsystems across manufacturing, factory operations, service, and sales verticals. Government and Fortune 500 advisor since 1987. Brings the commercial architecture that turns a strong technical proposal into a board-level decision Winnenden can defend.
Execution Team
Bogdan Toporan
20+ years leading engineering teams at Telenav, Micro Focus (HP), and Emerson, where he patented a SCADA communication system for the Oil & Gas sector. Bridges traditional IT and the AI revolution through two consulting brands: Arandi Software takes brittle monoliths to resilient, scalable cloud systems (Microservices, Kubernetes, AWS); Digitalize Today designs and deploys agentic AI, workflow automation, and intelligent document processing that actually works in production, saving hundreds of hours of manual labor.
Hardik Nakum
Over a decade across global financial institutions at the intersection of AI, cloud, and cybersecurity, driving enterprise transformation with a strong focus on resilience, governance, and long-term impact. Has led large-scale cloud and transformation initiatives across Azure, AWS, and GCP, supported multi-cloud re-architecture programmes, and helped leadership teams adopt innovation in a way that is practical, responsible, and aligned to business outcomes. Builds the next generation of enterprise systems where humans and AI work together.
Where the team has delivered
Mru Patel · internal change agent · Siemens Nixdorf merger
Delivery pedigree across the team · Siemens (Mru Patel — internal change agent during Siemens Nixdorf merger, McKinsey-selected) · GEC (industrial transformation) · IBM · Sun Microsystems · Lloyds Banking Group (Nico Fratila — 5 years network engineering) · Emerson (Bogdan Toporan — SCADA patent holder, Oil & Gas) · SAP · HP / Micro Focus · Vodafone.
Local & International Partners
Nautilus OT
OT cybersecurity · IndustrialOperational Technology cybersecurity specialists. 'Securing Your OT Future.' Tracks OT/ICS incidents across shipping, oil & gas, and manufacturing; publishes the OT Cyber Insights biweekly update.
The Engagement
Phase 1 first. Proof first.
Then Phase 2. Then Phase 3.
Start with a controlled Phase 1 that fixes blockers and proves value. Scale when the evidence says to. Stop any time — you keep everything.
Fix and Prove
A business intervention, not a training program · Below VP discretionary spend
10-Week Program
Assess & Align
Workflows, sponsors, systems access, blockers, governance map. Secure sandbox environment delivered inside your network.
Build on Real Workflows
We deliver 3-4 working agents on your priority use cases. Jira-based service triage, service diagnostics, procurement analysis — Kärcher chooses.
Architecture & Controls
Integration patterns, security baseline, human oversight policy, observability. Everything documented.
Decision Pack
Board-ready deliverable: KPIs, measured results, Phase 2 scope, cost, owners, and 18-month roadmap.
What You Get
3-4 Working AI Agents
Delivered on your real workflows. Owned by Kärcher.
Secure Sandbox Environment
Inside your network, behind your firewall. Ready for production expansion.
Board-Ready Decision Pack
KPIs, measured results, Phase 2 scope, cost, owners, and roadmap.
Architecture Blueprint
Integration map across your systems. What scales, what doesn't, what to fix.
Governance Baseline
Controls, audit trails, human oversight. Shadow AI visibility from day one.
Measured Workflow Improvement
Handle time, cost-per-resolution, accuracy. Evidence, not assumptions.
Operationalise & Integrate
From Phase 1 winners to production
Enterprise AI Operating Model
Governed, scalable, durable. Owned by Kärcher.
What we don't do
The boundaries,
up front.
A proposal is only as credible as its limits. These are ours — written down before a scoping call, not discovered mid-engagement.
No exfiltration of Kärcher data
All sandbox and production agents run inside Kärcher's network perimeter. No data leaves for training, evaluation, or analytics without explicit contractual basis and Kärcher DPO approval.
No access to payroll, HR, or personal finance systems
Phase 1 and Phase 2 scope explicitly excludes systems processing salary, medical, or private financial data. Those domains require specialist compliance pathways we don't propose here.
No replacement of existing vendor contracts
We deliver an AI layer on top of SAP, Kärcher Fleet, Brain Corp, Gemini, and your procurement tooling — not a rip-and-replace. Sunk costs protected.
No unsupervised high-stakes decisions
Agents do not autonomously approve spend, hire, terminate, contract, or communicate externally on Kärcher's behalf. Every high-stakes action routes through a human owner by design.
No long-term licence lock-in
Kärcher owns every agent, blueprint, and governance artefact. If you stop at any gate, you keep everything built to that point. No renewal required.
No Group rollout without Winnenden buy-in
Phase 1 is Romania-led on purpose. Scaling beyond is a separate conversation the Romania champion and Winnenden HQ agree on together. We don't push a subsidiary past its HQ.
Straight Answers
Questions you should be asking.
You're a small company. Can you handle Kärcher scale?
What happens if Phase 1 doesn't deliver measurable results?
Kärcher already has Google Gemini and SAP AI. Why go external?
What stops us from scaling this to other Kärcher markets?
€30K-€50K seems cheap for 'enterprise AI'.
Ready to start?
10 weeks. €30K-€50K based on scope. Working AI agents delivered on your real workflows.
Confirm a sponsor, choose the first workflows, and we start.
InfoAcademy × APEX OS: Winnenden, Germany · London, UK
Proposal valid for 90 days from delivery. Pricing subject to scope confirmation during the scoping call.
All comparative figures referenced on this site are based on publicly available analyst reports and industry benchmarks. Kärcher-specific statistics are sourced from publicly published Kärcher materials.
Data handling: All Phase 1 sandbox and Phase 2 production work is conducted inside Kärcher's network perimeter, under Kärcher's DPO governance. No Kärcher data is extracted for external training, evaluation, or analytics.