More than just hype: AI as a decisive factor
We make Google AI and Gemini your decisive factor: We connect Google Workspace and Google Cloud, bring AI to your teams' daily touchpoints and ensure that data and processes become measurable added value. And if your AI pilots have never made it to production: that is exactly what we build for — agents on one central platform, the Gemini Enterprise Agent Platform (GEAP), that actually deliver.
The questions that come up before every AI project
Almost every company has AI pilots by now — slick demos, enthusiastic workshops. And then? Most projects get stuck exactly there: in the pilot stage, without data grounding, without governance, without a central platform.
Concise answers to the four questions that come up in every decision process.
Why do so many AI pilots never reach production — and how do we change that?
Because most pilots are built as demos, not as products: without connection to real company data, without guardrails, without success metrics and without a platform to scale on. We build production-ready from the start — data grounding, safety guardrails and measurable KPIs are part of day one, not "later".
More details
For qualified projects, we assess funded proofs of concept via Google.
- Production-grade PoC instead of a demo: an agent on GEAP in a few weeks, on your real data with clear success criteria.
- Grounding & guardrails: answers from your sources instead of hallucinations, access cleanly controlled.
- The path afterwards is defined: from PoC to the central platform and into monitored operations — no pilot without a production path.
What is the Gemini Enterprise Agent Platform (GEAP) — and why not ten point solutions?
GEAP is Google's central enterprise platform for building, orchestrating, monitoring and governing AI agents — across all departments. Instead of ten point solutions with ten security models, you get one platform with central governance, access to Gemini and hundreds of models in the Model Garden, and grounding directly on your data.
More details
The platform carries the former Vertex AI capabilities forward under its new name. The difference shows in operations: every point solution needs its own access rules, its own monitoring, its own cost control. On GEAP you build the guardrails once — and every new agent inherits them. Orchestrated multi-agent workflows automate entire process chains instead of single steps.
- Central control: development, monitoring and governance of all agents in one place.
- Your data as the foundation: grounding on BigQuery & co. for precise, verifiable answers.
We are a Microsoft shop — is Google AI even worth it for us?
Yes — GEAP is vendor-neutral and also runs on M365 and Azure data landscapes, alongside Copilot and without a platform switch. Copilot assists in everyday Office work; GEAP builds the agents that automate your processes. The two are not mutually exclusive — many of our customers start exactly like this: with a pilot on their Microsoft data.
More details
- No rip-and-replace: your M365 environment stays, GEAP connects to the data.
- Alongside Copilot, not instead of Copilot: assistance and an agent platform solve different problems.
- Pilot as the entry point: a scoped use case on your data proves the value before you commit.
What does running AI agents cost — and how do the costs stay under control?
The honest answer: agents cause ongoing inference costs per request — and without steering, token consumption, quotas and model choice quickly grow out of control. That's why cost monitoring, budgets and the right GEAP edition are part of the architecture from the start — not of the first surprise invoice.
More details
- Edition consulting: the right GEAP edition for your needs — no over- or under-licensing.
- Cost guardrails: budgets, quota management and model choice per use case (not every problem needs the largest model).
- Managed AI Ops: ongoing monitoring of performance, token/inference costs, model drift and hallucinations.
Gemini and GEAP for Business
Gemini and the Gemini Enterprise Agent Platform (GEAP) are leaders in Gen AI. Gemini creates content at lightning speed while GEAP automates processes — so you stay competitive and quadruple your investment!
An overview of our focal areas
Security, Sovereignty & EU Compliance: In today's fast pace of AI, security is no longer an option, but a requirement. It is the foundation before Gemini & Co. come into play. We protect your AI environment with Google Cloud security standards and a consistent zero-trust architecture.
**Your protection:** Through consistent **sovereignty** you maintain full control over your data — your information is never used to train global models. Our solutions are “compliance-by-design” and comply with the **EU AI Act** as well as the **GDPR**. In this way, you use the latest technology with the security of sovereign, European data storage.
This also includes the right licensing: We advise you on the appropriate GEAP edition and Gemini tiers — so you neither over- nor under-license.
AI where you work
Gemini supports your teams directly in Gmail, Docs, Sheets, and Meetings.
Data-driven automations
GEAP uses your GCP data for accurate answers and autonomous workflows.
Secure, sovereign AI
Zero trust and EU compliance protect your intellectual property by design.
Our services
Depending on the initial situation, we provide targeted support in planning, implementation and development. Always structured, responsible and with a view to long-term benefits for your company.
AI Business & Readiness Check
From vision to robust plan in 72 hours. We analyze your IT, identify high-ROI use cases for Gemini and provide you with a ready-made roadmap for your AI rollout. Short, intensive and absolutely results-oriented.
Go to the AI business check →
Intelligent Productivity Gemini & G Workspace
We strategically introduce Gemini Enterprise, establish secure governance guidelines for your teams, and orchestrate automated workflows across platform boundaries. Efficient, secure and ROI-focused.
Google Workspace in smart →
Custom AI Solutions & GEAP
Develop solutions that don't come off the shelf. We build autonomous AI agents and fact-based knowledge systems on GEAP — seamlessly integrated into your processes and ready for productive use on an enterprise scale.
Tailored AI agents →When an agent platform is not the right first step
We don't sell AI for AI's sake. We address these three situations openly in the intro call, before you invest:
No data foundation
Agents are only as good as the data they stand on. If your data sits in silos or the quality is questionable, we build the foundation first — a clean data platform — and then the agents on top. The other way around, you burn budget.
You only need text assistance
If it's about drafting emails, summarizing meetings and writing documents, Gemini in Google Workspace is enough — already included from Business Standard. You don't need an agent platform for that, and we'll tell you so.
Agents without governance
An agent without owners, guardrails and ongoing monitoring turns from a productivity gain into a risk. Without readiness for governance and operations, we advise against the rollout — or take on both as a managed service.
Not sure where you stand? That's exactly what the free intro call is for — an honest assessment, no strings attached.
Free intro callGoogle AI & AI agents — answered briefly
How quickly can a first AI agent be used productively?
A production-grade proof of concept on GEAP is up in a few weeks — connected to your real data, with guardrails and defined success criteria. After that, you decide on the basis of measurable results whether and how to scale. For qualified projects, we assess funded PoCs via Google.
Is our data used to train Google models?
No. In Google Cloud's enterprise offerings, your content and prompts are not used to train global models — your data remains your data. We additionally configure data residency and access controls according to your risk requirements and document it audit-ready.
What is the difference between Gemini in Workspace and GEAP?
Gemini in Workspace is the AI assistance in everyday work — in Gmail, Docs, Sheets and Meet, included from Business Standard. The Gemini Enterprise Agent Platform (GEAP) is the platform underneath: on it, you build, orchestrate and monitor your own AI agents that work on your company data and automate entire processes. One you use, the other builds for you.
Does GEAP also work with our Microsoft and Azure data?
Yes. GEAP is vendor-neutral and integrates with existing M365 and Azure data landscapes — alongside Copilot, without a platform switch. Especially in Microsoft-centric companies, a scoped pilot on the existing data is the typical entry point.
Can AI agents be operated in compliance with GDPR and the EU AI Act?
Yes — with the right setup: EU data regions, access controls, documented data flows and a processing register for your agents. We build compliance-by-design and, on request, set up ongoing agent governance — registry, drift control and audit-ready reports.
Which GEAP edition do we need?
That depends on your use cases, expected volume and governance requirements. We advise you on the right edition and Gemini tiers so you neither over- nor under-license — and procure the licenses for you on request, from a single source.
Who monitors the agents in ongoing operations?
Either your team — enabled by us — or we do, as your Managed AI Ops partner: ongoing monitoring of agent performance, token and inference costs, model drift and hallucinations, plus continuous prompt and model optimization. That keeps quality and costs permanently under control.
Our innovation cycle for your AI agents
Four phases — from the first use case to monitored agent operations. This is exactly how we'll work with you:
1. Strategy & use cases
2. Foundation & PoC
3. Rollout & enablement
4. Operations & optimization
- •AI Business & Readiness Check
- •ROI-prioritized use-case list
- •GEAP edition & license consulting
- •Prioritized roadmap
- •GEAP setup & governance guardrails
- •Data grounding on your sources
- •Production-grade PoC (funded, if qualified)
- •Defined success criteria & KPIs
- •From PoC to production
- •Multi-agent orchestration
- •Gemini enablement & adoption
- •Change management from day one
- •Managed AI Ops
- •Token & inference cost control
- •Drift & hallucination monitoring
- •Continuous prompt & model optimization
