Problem
Incoming inquiries must be read and sorted manually.
Approach
AI-assisted classification, extraction of key data and routing to the right place.
Outcome
Faster response and less manual groundwork.
Service · AI & automation
AI Automation that saves you real time every day
TeaFan Media helps companies in Germany and beyond eliminate time wasted on manual tasks like emails, data entry, follow-ups, and tool switching. We identify practical automation opportunities in your workflows and build AI solutions that connect your existing tools — instead of creating more complexity.
Python
GitHub Actions
API
Human Review
In person – Rhine-Main area
Face-to-face meetings are always possible in and around Wiesbaden, Mainz and Frankfurt.
Remote – across Germany & worldwide
Everywhere else we collaborate smoothly online — in English or German.
Typical Use Cases
- Your team regularly copies data between email, spreadsheets, CRM and tools.
- Inquiries have to be read, sorted, answered or forwarded.
- Reports, summaries or status updates are created manually again and again.
- After meetings, follow-ups, CRM notes or quotes are left undone.
- You know AI could help but don’t want a sprawl of tools.
- A process lives in individual people’s heads but isn’t documented.
What you get
From analysis to ongoing operation – small, verifiable steps instead of big AI promises.
Core building blocks
Process audit
Flow, people, tools, exceptions and risks — recognising realistic automation limits.
AI-readiness check
Data quality, access, data protection and tool maturity — clarifying whether AI truly fits.
Tool & data map
Systems, interfaces, data flows and permissions — less flying blind before delivery.
Workflow blueprint
Target process, triggers, rules and control points as a clear build spec.
Prototype
A small workflow with real sample data — early validation without a big platform project.
Integration
API, n8n, Make, custom code or existing tools — automations fit your environment.
Optional add-ons
Human review
Check steps, approvals and error cases — control stays where it’s needed.
Documentation
Flow, access, maintenance and edge cases so the workflow stays comprehensible.
Training
A short onboarding for users and owners so the team can work with the system.
From audit to ongoing optimization
Three ways to work together – depending on maturity and need.
Audit
- Best when
- You don’t yet know where automation pays off.
- Typical scope
- Process analysis, prioritization and a roadmap.
Core Package
Workflow project
- Best when
- A concrete use case is clear.
- Typical scope
- Blueprint, prototype, build and handover.
Ongoing optimization
- Best when
- Workflows become business-critical.
- Typical scope
- Monitoring, adjustments and new automations.
Project Examples
Problem
Follow-ups are left undone after client meetings.
Approach
Meeting summary, task list and a draft follow-up email.
Outcome
Less rework and better follow-up communication.
Problem
Quotes are built from recurring information.
Approach
Structured input, a quote draft and human approval.
Outcome
Faster quotes without losing control.
Problem
Reports are regularly compiled from several sources.
Approach
Automatic data retrieval, summary and delivery to defined recipients.
Outcome
Less routine and more reliable timeliness.
How we work together
- 01
Audit
Clarify processes, bottlenecks, tools and risks – usually in 30 minutes.
- 02
Blueprint
Target process, triggers, rules and control points as a clear build spec.
- 03
Prototype
One scoped use case made testable early – low-risk and concrete.
- 04
Build
A production workflow built on your existing systems – maintainable and documented.
- 05
Handover & care
Onboarding, monitoring and – optionally – ongoing adjustments.
Frequently asked questions
What can sensibly be automated?
Recurring tasks with clear inputs, rules or decision patterns: moving data, sorting emails, preparing follow-ups, compiling reports, generating documents or summarising information.
Where is AI not the right fit?
When the process isn’t understood, data is very messy, or every decision needs real expert judgement without a recurring pattern. Then clarifying the process matters more than an AI tool.
Do we need new software?
Often not. Existing tools and interfaces are reviewed first. New software is only recommended when it genuinely simplifies the workflow or existing systems don’t allow clean integration.
How do we best start?
With one clearly scoped use case that costs noticeable time and is easy to verify. A small working workflow is worth more than a large AI roadmap without delivery.
How do you handle credentials and sensitive data?
Access is granted as narrowly as possible, ideally via separate accounts, API keys or approvals. Data protection, permissions and data flows are clarified before implementation.
What happens if an automation fails?
For relevant workflows, error cases, notifications and manual fallbacks are planned. An automation should not fail silently but stay verifiable.
Who owns the workflow after delivery?
Ownership, hosting, tool accounts and documentation are clarified up front. The goal is a clean handover, not a black box only the provider understands.
Can existing n8n, Make or Zapier workflows be improved?
Yes. An audit of existing automations is often worthwhile, because many workflows work as a demo but become unstable with real data, edge cases or changes.
Do you offer ongoing support?
Yes. When a workflow is used regularly, support makes sense: monitoring, adjustments when tools change, new build-out stages and occasional process reviews.
Related pages
Where do you lose the most time today?
Describe one bottleneck – we’ll see whether automation is worth it.