AI FOR BUSINESS
Office work often starts with searching, copying information and asking for missing details. AI can help review documents, prepare enquiries and make information easier to find. We develop a solution for your business and connect it to the tools your team already uses.
In customer service, administration or out in the field: What matters is which task becomes easier. These examples show where AI can help and what needs to be agreed before using it.
Invoices and receipts need not be typed in field by field. AI can extract details, sort documents and suggest matching bank transactions.
Unclear details need review; tax assessment remains with the tax adviser.
For exampleInvoicesReceipts
An assistant answers questions about the current case, finds relevant information and prepares next steps. Your team can stay in the working screen more often.
Its task determines which data it may see and which actions it may perform.
For exampleAdministrationCase handling
Manuals, internal guidance and project documents become easier to use. Your team can ask a question and receive an answer with relevant sources to review.
Sources must be current and approved. Document search does not eliminate incorrect answers.
For exampleService knowledgeInternal processes
Visitors can learn about services and processes outside office hours too. A chat answers common questions and points people to the right contact when needed.
Binding commitments and individual quotations need an agreed route to your team.
For exampleService questionsGetting in touch
A bot can capture enquiries in WhatsApp or collect internal questions in Slack. Information arrives in a more structured form, making the request easier for your team to understand.
The channel, data access and handover to responsible people are configured for the intended use.
For exampleWhatsAppSlack
An agent can read an enquiry, compare details from permitted sources and prepare a case. This reduces some of the searching between different programs.
Consequential actions need technical limits and approval rules before execution.
For exampleIncoming enquiriesPreparation
An assistant can refer to approved agreements and earlier work steps. Your team spends less time explaining the same background again.
What is stored, who may access it and when it is deleted need clear rules.
For exampleProject knowledgeOngoing cases
When coding agents extend software, validation rules can run before additional packages are installed. Suspicious dependencies can be identified earlier.
These checks reduce risk, but do not replace other testing or security reviews.
For exampleDevelopmentCoding agents
When several assistants and people are involved, a shared overview helps: Who triggered a step, what was approved and where does the task stand?
Permissions and rules must be enforced outside the language model.
For exampleApprovalsAction logs
Long emails, meeting notes and analyses can become a readable summary. Open questions and unusual values can be gathered for further review.
Figures must come from reliable sources. A summary alone does not establish a cause.
For exampleMeetingsMonthly reports
Field staff can capture documents by phone, answer questions or prepare notes for the office. Information needs to be copied over again less often.
Access, connectivity and approvals are considered for mobile use too.
For exampleField workiPhone and Android
AI can interpret differently worded text and prepare details. Fixed rules then handle routing, validation or filing. AI and conventional automation complement each other.
Conventional software is often enough for clear rules that require no interpretation.
For exampleHandoversRoutine tasks
A bot can compile campaign data and propose budget or bid changes for review. Your team gets a basis for decisions without opening every report individually.
Budget changes and other consequential actions need appropriate permissions and agreed approvals.
For exampleGoogle AdsCampaign reports
A voice assistant can take questions and consider approved images. This can help when typing is awkward or a photo explains the situation more clearly.
Camera, microphone and storage access are granted deliberately. Interpretation can be wrong.
For exampleVoice interactionImage-based help
An ongoing conversation can receive relevant extra information, such as an approved location or a device’s current status. Less background needs to be explained aloud.
Which data is provided and when a notification is triggered are agreed in advance.
For exampleLocation contextSensor information
An assistant can collect the reason for a visit and contact details, offer a booking route and check availability through a connected calendar. This can reduce back-and-forth emails.
Whether it books directly or forwards a request depends on the integration and booking rules.
For exampleService callsViewings
An AI feature should fit into your workflow. We clarify what it prepares, who decides and which steps follow fixed rules.
01 · AI
AI reads text, interprets details and prepares a suggestion. The supporting sources help your team review it.
An enquiry with relevant documents and a draft reply
02 · TEAM
Your team reviews results where professional judgement is needed. You define which actions require approval before they happen.
Review a commitment and approve sending it
03 · SOFTWARE
The software handles calculations, validation rules and permitted changes. Access controls limit which actions an AI feature can trigger.
Calculate amounts and save an approved transaction
Our own products illustrate different uses. They offer an insight; your solution will be shaped by the tasks in your business.
CynTax collects receipts and asks for missing documents relating to a payment. Fibi helps resolve open questions in the app. Suggestions are reviewed and confirmed; tax assessment remains with the tax adviser. CynTax is in its pilot phase.
Leah supports admins in stempeln.at with balances, unusual entries and reports. We use a dedicated test corpus for the answers. The software’s calculation engine computes allowances. Conversation and calculation work together, while the calculation rules remain defined.
The chat draws on this website’s content and helps with questions about our services. For a personal conversation, it links to our booking calendar. You can check its answers against the linked sources.
SafeInstall checks software packages before installation and blocks them according to defined risk rules. This supports teams working with coding agents. The source code and documented limitations are publicly available.
AgentGuard, Continuity Core and ACPIP are on the engineering page. Go to the engineering page
Before working with business data, we clarify the sources, access rights and processing terms.
We select the documents and fields required for the task. Unnecessary or particularly sensitive details can be excluded or removed beforehand.
You know which providers and services are involved. The model, plan and settings are chosen to suit the task and your requirements.
We check storage and processing locations for the services involved. Whether regional processing is available depends on the selected service and its features.
Retention, deletion and any use for model training are checked against provider terms and settings. Using your documents as a knowledge source does not in itself require training the model.
Access rights and logs are configured for the relevant roles. We also define which content is logged and how long it is retained.
We start with a specific workflow. Relevant cases help assess whether the solution is useful and how much review it needs in daily work.
In a free initial conversation, you show us where work gets held up or repeats itself. This identifies the first area to focus on.
We review existing sources, programs and integrations. Data access and processing are agreed before testing.
Approved examples help us assess results, failure cases and the work needed for corrections. This makes the benefit tangible.
We set up responsibilities, approvals and handovers. Your team knows how to handle results and exceptions.
Usage and results are monitored after introduction. Content, integrations and rules continue to need maintenance.
That depends on the provider, the service plan and the agreed settings. We check these terms before using your data. Your documents can support search and answers without retraining the model. That alone does not determine how a provider stores or uses the data.
No. We first look at what you have: documents, emails, databases or existing programs. Important content needs to be current, understandable and accessible for reliable answers. The specific task determines what needs updating, cleaning up or adding.
That depends on your programs’ interfaces, access rights and export options. We check which data can be read and which changes may be allowed. This shows whether direct integration is possible or whether an approach such as file exchange makes more sense.
The effort depends on the task, data sources, integrations and required checks. After the free initial conversation, you receive a fixed-price offer for the agreed scope. Ongoing costs for model usage, infrastructure and support are listed separately.
AI can misunderstand information, miss details or produce an answer that sounds convincing but is wrong. We therefore test the solution with relevant cases and set up sources, approvals and limits for its intended use. Professional review remains important for consequential decisions. Tests and controls reduce risk, but do not guarantee error-free results.
No. Conventional software is often better for fixed calculations, clear rules and unchanging workflows. AI is particularly relevant when processing language, documents or enquiries phrased in different ways. A suitable solution often combines both approaches.
Bring us a task from your working day. Together, we can look at which solution would help your team, how it would fit your existing programs and what it would take to build.