Process automation
Automate recurring tasks, documents, and internal workflows so teams spend less time on manual follow-up.
AI consulting and implementation for SMEs
AI only creates value when it reaches the workflow.
Many companies know AI matters. The harder question is where it makes commercial sense, which data and systems are ready, and how the idea becomes software people actually use. That is where 1tm works.
- We find workflows where AI can create concrete business value
- We check data, risk, and integration effort before implementation
- We build production-ready software, not isolated AI demos
Trusted context
20+ years in software engineering
German GmbH
SME and B2B focus
Privacy-aware implementation
01
For workflows where time, knowledge, or data has become the bottleneck
AI becomes useful when existing work is already expensive, slow, or hard to scale. We turn those bottlenecks into practical use cases and systems that can be integrated.
Customer service and knowledge systems
Build assistants and search systems that derive answers from verified company information.
Research and lead signals
Evaluate market, press, and web signals systematically so relevant opportunities become visible earlier.
Data and reporting
Organize data sources, automate recurring analysis, and prepare better operational decisions.
Web and cloud integration
Embed AI where employees and customers already work: portals, web apps, and business software.
Product and marketing workflows
Make product data, content, and e-commerce workflows more scalable without giving up quality control.
02
Our mechanism: from bottleneck to production AI system
We do not sell abstract AI strategy. We guide you through a clear delivery path: isolate the problem, test the value, reduce the risk, build the solution, improve the operation.
01
Find the bottleneck
We identify tasks where manual work, search effort, data quality, or response time creates real cost.
02
Test value and feasibility
We assess value hypothesis, data readiness, technical dependencies, privacy, and integration effort.
03
Build the pilot
We validate the business case with a focused prototype or MVP before the idea becomes a larger project.
04
Integrate into systems
We bring the solution into existing workflows, data sources, web applications, and operational processes.
05
Improve impact
After launch, we improve quality, adoption, and economics based on real usage.
03
Where the mechanism is already useful
These examples are not technology showcases. They show recurring patterns: structure work, make knowledge available, and accelerate decisions.
Product descriptions for online shops
Context
Many items need consistent copy; manual creation slows assortment and content operations.
Solution
We built an AI-enabled workflow for automated, search-friendly product description creation.
Result
Recurring copy work became a faster, more consistent, and easier-to-integrate process.
Chatbots for support and websites
Context
Customers and prospects expect fast orientation while knowledge is spread across websites and internal sources.
Solution
We designed chatbot solutions that can use verified external and internal information in a controlled way.
Result
Answers become more consistent, easier to find, and better embedded in the customer journey.
News analysis for sales signals
Context
Relevant market and news signals appear continuously, but manual monitoring is hard to run reliably.
Solution
We implemented an AI-supported web application for topic monitoring and automated reports.
Result
Manual research became a structured, repeatable analysis workflow for sales and market observation.
04
Why AI projects depend on implementation, not just models
The model is rarely the whole problem. The real question is whether data, workflows, privacy, adoption, and operation fit together.
Privacy and sovereignty
Before sensitive information is processed, we clarify data flows, model access, and integration points.
Respect existing IT
We build solutions so they fit current systems, teams, and workflows.
Business value
Every implementation needs a clear business function, not just an impressive demo.
Work with domain teams
The best technical approach combines software expertise with the process knowledge of your domain teams.
05
For companies that need more than advice
1tm combines AI consulting, software architecture, web development, and B2B process understanding into a team that can deliver.
Martin Schubert
CEO | AI consulting, development, and business strategy
Develops AI strategies and technical solutions that fit real business workflows.
LinkedIn
Toni Thomä
CTO | AI engineering and software architecture
Turns complex AI technology into robust, usable applications.
LinkedIn
Markus Wahl
Software development, marketing, and B2B/e-commerce
Connects implementation work with product, market, and communication needs.
LinkedIn
Thomas Wild
E-procurement, SAP, and B2B solutions
Contributes experience in procurement workflows, SAP, and e-commerce integration.
06
Questions to settle before an AI project starts
Good AI projects do not start with a tool. They start with clear decisions about value, data, integration, and operation.
How do we identify an AI project with commercial value?
A useful AI use case reduces specific process costs, accelerates recurring decisions, or makes existing knowledge more reliable. We assess the bottleneck, data readiness, risk, and integration effort first.
Do our data need to be perfectly prepared?
No. Many projects start with a realistic data assessment. The important question is which data are needed for the first valuable use case and how quality, access, and privacy can be controlled.
Does 1tm only build prototypes, or production systems too?
Our focus is implementation. A pilot validates value and feasibility. After that, we integrate the solution into existing web applications, data sources, portals, or operational workflows.
Which companies are the best fit?
We mainly work with mid-sized B2B companies that have a clear process problem, existing systems, and the goal of bringing AI into daily operations in a controlled way.
For internal orientation
These materials help teams talk about AI potential internally. The real assessment starts with your workflows, data, and systems.
07
Find out where AI makes commercial sense in your business
Briefly describe your company, one workflow, or a concrete challenge. We will assess whether it should become an AI use case, a pilot, or first a better foundation.