AI solutions · Systems integration · Company knowledge
The enquiry is in.
So is the answer.
We connect emails, documents and your ERP or CRM with AI. Your team gets a draft reply with sources, reviews it and sends it. For technical B2B companies in sales and service.
30 minutes · free of charge · directly with Martin Trixner
Example · Sales inbox
Maintenance, North plant
08:42
Replacement pump for system A17
“We need a replacement pump for system A17. Does the P24 version fit?”
- Inbox Previous email thread
- Document Pump enquiry checklist
- ERP System data A17
Draft reply ready · 3 sources
Hello, our records show a DN 50 connection size for system A17. To check P24, we still need the medium and flow rate.
Example with prepared data, no live AI.
A quick calculation
How much time goes into searching for information?
Three rough estimates. The result shows how much time your team spends each month searching for and gathering information. How much of it AI can take on is something we clarify in the initial call.
32hours a month currently go into searching and gathering information.
A rough calculation from your inputs, with 4.33 weeks per month. It runs only here in your browser.
Getting started
One specific question.
A suitable way to start.
If clarity is missing at first, we review a defined area. Scope and result are fixed before you commission us.
Your quotation handling takes too much time
Quotation Process Assessment
We review 3–5 technical customer enquiries. You receive a written basis for decision-making and a clearly scoped pilot plan.
€1,900 excl. VAT
10 working days after kick-off and receipt of all documents
Your input: about 3–4 hours
You want to find worthwhile AI applications
Compact AI opportunity assessment
We compare up to five AI applications in one business area. You receive a reasoned prioritisation and next steps.
€1,900 excl. VAT
10 working days after kick-off and receipt of all documents
One area · up to five applications
Is your task already clear?
We discuss development and integration directly. Scope, price and operation are agreed for your project.
The assessments do not include development or ongoing operation. A pilot is a possible next step.
Your task decides
Where is your team
missing the bigger picture today?
Company knowledge, quotation preparation and systems integration can each be a starting point. We clarify where AI actually helps.
01
Knowledge found
and backed by sources
Search manuals and service knowledge. Prepare answers with matching sources and defined access rights.
OutcomeA usable AI knowledge base for your area of work.
02
Technical enquiries
prepared
Bring together requirements from emails and attachments. Flag missing details and create a basis for the draft quotation.
OutcomeA reviewable case for sales and the specialist team.
03
Existing systems
connected
Transfer data between website, customer management and ERP. Prepare recurring work according to defined rules.
OutcomeA connected workflow with clear responsibilities.
Practice & experience
What is already running.
What an example shows.
A client project in production, an in-house test and a product in development carry different weight. Here you can see where each one stands.
Client project · in production
RAG chatbot for APIORIUM
A website assistant uses its own knowledge base: documents are prepared, relevant content is retrieved and used for AI answers.
- Prepare documents
- Retrieve relevant content
- Prepare an answer from the retrieved content
RAG means: the AI draws relevant content from a knowledge base for its answer. The case demonstrates this workflow; no time or revenue effect is claimed here.
Document AI · in-house
61 / 61
invoice numbers read correctly in the test described.
The figure refers to the invoice number field. It is not an accuracy figure for all invoice data and not a measured time saving.
Narrowly scoped technical proof
Martin Trixner Founder and Technical Lead
Your contact in Linz
Talk to me about
the implementation, too.
Since 2002 I have been developing digital processes, applications and interfaces. I bring this experience to connecting your existing systems with AI.
My recommendation: we first look at a typical enquiry, a knowledge question or a duplicate data entry. From that, a concrete next step can be derived.
TRIXNER AI Workspace · in development
A product in development
to try out.
The Workspace is designed to connect emails, company knowledge and customer management. The public demo shows the workflow. In the personal test, AI analyses and draft replies are created with sample data; sending and external actions are simulated.
Public preview without sign-up.
Personal test after email confirmation.
Before we start
The questions behind
an AI project.
Do we have to replace our existing systems?
We first check the existing interfaces and data sources. Whether and how your software can be connected is clarified in the specific project.
Who reviews answers and draft quotations?
Your specialist team remains responsible for technical approval. Together we define which work may run automatically for each workflow.
What happens to our documents?
Before implementation we clarify access rights, processing and operation. Client documents do not go to external AI services without an explicit agreement.
And if the workflow does not need AI?
Then that is part of the recommendation. A fixed rule or an interface can be enough for the task.
Free introductory meeting · 30 minutes
Which work step
is holding your team up?
Bring a typical situation from sales, service or administration. We clarify a possible approach and the right way to start.
Would you like to get your bearings first? Free process check: five questions, no email required ↗