Knowledge management software that asks for the knowledge itself
Wikis and knowledge bases are good repositories for knowledge that someone writes down. wissa.ai starts one step earlier: an AI interviews your knowledge holders in a chat, about 15 to 20 minutes per conversation, and turns their answers into structured documentation with a source for every statement that grows with every further conversation.
The free trial package with 10 credits is usually enough for one interview including the analysis. It is valid for one month, once per company, with company details and DPA, while the allocation lasts.
Hosted in Germany · AI processing in the EU · DPA under Art. 28 GDPR · Materials for your works council
Checking and approving incoming invoices
- Purpose: Check incoming invoices, approve them and book them on time
- Frequency: ongoing, monthly closing
- Tools used: Invoice list (Excel), DATEV
Recording incoming invoices
Sort post and email, record in the invoice list “In the invoice list I fill in date, supplier, amount and status.”Martina Krüger · Interview 1 · Question 2
Still open
- being asked What triggers the booking in DATEV?
- being asked Who checks when Ms Krüger is on holiday?
What knowledge management in a company depends on
Many mid-sized companies have a wiki, a SharePoint or a folder called “Handbook”. The interesting question is who puts the knowledge in and who keeps it current.
The people who know have no time to write
The most valuable knowledge sits with experienced staff: in the warehouse, on the shop floor, in field service, in accounting right before month-end. For them the day-to-day work comes first, and rightly so. A 20-minute conversation still fits in nicely.
Experience is hard to write down
The exception for the key account, the call to the supplier before the order goes out, the trick on the machine: whoever has done it for years no longer thinks about it. Tacit knowledge rarely comes to mind while writing, and a well-placed question brings it out.
Trust comes from being current
People who trust an instruction look it up again next time. For that, every knowledge base needs a fixed trigger for updates; otherwise people go back to asking a colleague.
How wissa.ai works: from interview to documentation
The AI asks, and your team reads and corrects. The work shifts from writing to reading, which is much faster.
- 01
Start with one responsible person
A first chat interview covers the department, main tasks and systems, and asks who really knows how things are done.
approx. 12 minInterview · Goods receipt
Tap an answer - 02
The AI works its way from expert to expert
Once you approve, colleagues who are named receive a personal invitation link, no account needed. The questions build on what has already been said, in the chat, and can be paused at any time.
Needs you · 3
- Aylin Kayawaiting for your approvalnamed by Bernd Vogel
- Ms Albrechtaddress missingnamed by Martina Krüger
- Mr Wilkensaddress missingnamed by Holger Brandt
- 03
Follow-up questions where an answer leaves a gap
Special cases, cover arrangements, workarounds next to the ERP: the AI follows up wherever something is still missing. If two statements contradict each other, both are shown side by side with their source.
Contradiction
Approval path for invoices over €5,000
Mr Vogel and Ms Krüger describe the approval path differently. Choose what applies.
Docs · Approval over €5,000still open, being clarified - 04
Documentation that grows with you
The conversations produce process descriptions, an overview of all areas and processes, an org chart and onboarding plans. Every further interview updates the documentation, with changes visible as a diff, and a handover link shares the current state with a successor.
WarehouseDeputyNobody stands in for the warehouse manager.→ The analysis suggests naming a deputy.
Try it: every view is rebuilt from the app. Content from the demo workspace “Muster GmbH”, all names fictional.
What the software actually delivers
A body of knowledge that comes out of conversations and grows with every further one.
- Step
“When I'm on holiday, Ms Krüger approves up to 5,000 euros.”
Interview 2 · Question 2 ● confirmed - Tool
“The tax office sets up DATEV access; activation usually takes two days.”
Interview 2 · Question 4 - Handover
“I put checked invoices into Ms Krüger's ‘For payment’ folder.”
Interview 1 · Question 3 ● confirmed - Pain point
“Just before month-end closing we often hunt for delivery notes still lying in the warehouse.”
Interview 1 · Question 7
Interviews in a chat
About 15 to 20 minutes per conversation, with no preparation at all. Tappable answer suggestions make it easy to start, and screenshots or photos can be attached right away.
A source for every statement
Every statement in the documentation can be traced back to its source, usually the conversation it came from. That lets the department check every statement.
Contradictions made visible
“Runs through SAP” versus “runs through three spreadsheets”: both statements appear side by side, and you decide with one click which one holds. Documentation and graph follow.
Knowledge risks identified
Which task is known by only one person? The analysis shows knowledge silos and the bus factor per process, and with them the order in which you secure knowledge.
An org chart based on how people actually work
Who works with whom, who hands over to whom, where a role is vacant: the org chart grows out of the interviews.
Onboarding plans per role
Processes in learning order, systems together with the colleagues who master them, and contact persons. New hires can look things up whenever a question comes up.
Knowledge management tools compared
The tools differ above all in one basic question: who puts the knowledge in, and what keeps it current? Every category has its place, and they often complement each other.
| Criterion | Wiki | BPMN modeller | Screen recording tool | wissa.ai |
|---|---|---|---|---|
| Who puts the knowledge in? | Everyone writes for themselves | A trained person models the process | Whoever performs the task on screen | The AI asks the knowledge holders in conversation |
| Strength | Storage, structure, search, permissions and versions | Precise, standardised process diagrams | Click-by-click guides with screenshots in minutes | Gets experience and exceptions out of people's heads |
| Limitation | Relies on someone writing | The notation takes practice to read | Focuses on operating software on screen | No diagram editor and no click-by-click guides |
| Effort for knowledge holders | Writing time, spread across all authors | Workshops with the person who models | Low, as long as the work happens on screen | About 15 to 20 minutes per conversation |
| Stays current through | Regular upkeep by the authors | Remodelling after every change | Re-recording when the interface changes | Further interviews, changes shown as a diff |
wissa.ai
- Who puts the knowledge in?
- The AI asks the knowledge holders in conversation
- Strength
- Gets experience and exceptions out of people's heads
- Limitation
- No diagram editor and no click-by-click guides
- Effort for knowledge holders
- About 15 to 20 minutes per conversation
- Stays current through
- Further interviews, changes shown as a diff
Screen recording tool
- Who puts the knowledge in?
- Whoever performs the task on screen
- Strength
- Click-by-click guides with screenshots in minutes
- Limitation
- Focuses on operating software on screen
- Effort for knowledge holders
- Low, as long as the work happens on screen
- Stays current through
- Re-recording when the interface changes
BPMN modeller
- Who puts the knowledge in?
- A trained person models the process
- Strength
- Precise, standardised process diagrams
- Limitation
- The notation takes practice to read
- Effort for knowledge holders
- Workshops with the person who models
- Stays current through
- Remodelling after every change
Wiki
- Who puts the knowledge in?
- Everyone writes for themselves
- Strength
- Storage, structure, search, permissions and versions
- Limitation
- Relies on someone writing
- Effort for knowledge holders
- Writing time, spread across all authors
- Stays current through
- Regular upkeep by the authors
Simply keep using your existing company wiki, and wissa.ai adds the knowledge that so far has lived only in people's heads. Whoever likes to write keeps writing, and everyone else answers questions in the chat.
When wissa.ai is a good fit
A good fit if …
- Knowledge sits with people who would rather answer questions than write documentation
- A resignation, a retirement or a succession is coming up
- New hires keep asking the same questions
- A wiki exists but is outdated or half empty
- Companies with roughly 10 to 250 employees whose processes have grown over time
Less of a fit if …
- You are looking for a plain intranet with a news feed and a canteen menu
- You need illustrated click-by-click guides for a single application, which is what screen recording is built for
- Your processes run entirely inside one system and need to be measured, which is what process mining is for
What it costs
Billing runs on interview credits: about 10 credits equal one completed interview including the analysis on average, billed by actual AI usage. Respondents need no account of their own, Starter and Business can be cancelled monthly, and Enterprise offers more capacity on request.
- 10 credits, usually enough for one interview to try it out
- Valid for 1 month, ends automatically
- Once per company, with company details and DPA, while the allocation lasts
- 100 credits per month - about 10 interviews
- Cancellable monthly
- For small teams and getting started
- 250 credits per month - about 25 interviews
- Cancellable monthly
- Room for follow-up interviews and freshness checks
Need more capacity?
On request- Credits and user seats in the amounts your team needs
- Pay on invoice with payment terms
- Personal onboarding in the first month and direct support
- DPA and documents for data protection and the works council
Additional credits€79 per 100 creditsValid for 12 months · Available whenever you need them · Usable while a subscription or the trial package is running
- About 10 credits are roughly one completed interview - including the analysis and the documentation update. Billing follows actual AI usage: short conversations cost less, long ones more.
- Respondents need neither an account nor a licence of their own, however many you invite. Their interviews run on your company's credit balance.
- Subscription credits apply to the current month, additional credits for twelve months.
- A free trial package for businesses to get to know wissa: 10 credits, usually enough for one interview including the analysis, valid for one month and once per company, while the allocation lasts. You enter your company details, accept the terms and conclude the data processing agreement, no payment details needed.
wissa is made for businesses. You choose your package in your account and pay by credit card, SEPA direct debit or PayPal, or on invoice after a short request if you prefer. Invoices arrive as PDF. All prices net, plus VAT.
Further reading in our guides
Practical guides on knowledge management, knowledge bases and knowledge transfer, whichever tool you use.
Implementing Knowledge Management: 7 Methods
How to implement knowledge management in a company: five steps, seven knowledge management methods compared and the mistakes to avoid.
Read article →How to Build a Knowledge Base: Structure, Steps, Software
How to build a knowledge base and structure it: a five-step rollout, a sample structure to copy and software from wiki to AI interview.
Read article →Knowledge Transfer: 7 Methods Compared
Knowledge transfer in companies: seven methods from handover interview to AI interview, with effort, strengths and limits, and how to choose one.
Read article →Tacit Knowledge: Examples & Methods to Capture It
What tacit knowledge is, examples from everyday work, and which questions make experience-based knowledge explicit - with an interview guide.
Read article →Is your focus on processes?
If you want to document processes, digitise work instructions or structure onboarding, the page on process documentation software shows what wissa.ai delivers for that.
Process documentation software →Frequently asked questions about knowledge management software
What is knowledge management software?
Software that captures, organises and makes a company's knowledge findable: processes, instructions, contact persons and lessons learned. Most tools, such as a wiki, knowledge base or intranet, take care of storage and search. wissa.ai takes care of the step before that: capturing the knowledge through interviews in the first place.
What kinds of knowledge management tools are there?
Roughly four categories: wikis and knowledge bases where everyone writes for themselves; document repositories such as SharePoint or a network drive; modelling tools for process diagrams; and screen recording tools that produce click-by-click guides. AI interviews as in wissa.ai are a fifth category: here the software asks the questions itself.
Is wissa.ai a knowledge management system or knowledge base software?
Only partly either. Knowledge base software is a repository with search, permissions and versions, and a knowledge management system combines such repositories with responsibilities and routines. wissa.ai comes before that and captures the content: the AI interviews your experts, and their answers become documentation with a source for every statement, which you read in the app and share via a handover link. You keep your wiki or knowledge base alongside it for everything your team writes down anyway.
Does wissa.ai replace our wiki?
wissa.ai complements your wiki. A wiki is a good place for knowledge that someone writes down, and wissa.ai captures the knowledge that rarely gets written down in everyday work, often because people do not realise how much they know. The two run well side by side.
How do I introduce knowledge management in my company?
Start with the topics whose loss would hurt most: note which task stops when a particular person is absent, and begin there. Give every area a responsible person and a trigger for updates. Digital knowledge management then comes down to two things: a place where the knowledge lands, and a way for it to get there. Our guide on implementing knowledge management walks through the approach step by step.
Do our employees need to create an account?
No. Respondents receive a personal invitation link and can answer straight away in the chat. Only the people who manage the documentation and approve invitations need an account.
What about data protection and the works council?
wissa is built for GDPR-compliant use: hosting in Germany, AI processing in the EU and a data processing agreement under Art. 28 GDPR that lists all sub-processors. The interviews describe workflows, roles and systems, and wissa does not assess people. Using wissa usually requires co-determination; for involving the works council, the app provides a package with the flow and sample questions of the interviews. We recommend making participation voluntary.
What does the knowledge management software cost?
Starter costs €79 per month with 100 credits (about 10 interviews), Business €149 per month with 250 credits (about 25 interviews), both cancellable monthly. For more capacity there is Enterprise, price on request. To try it, there is a free trial package with 10 credits, usually enough for one interview including the analysis (once per company, valid for one month, with company details and DPA, while the allocation lasts). Respondents need no account of their own. All prices net, plus VAT.
Secure the first knowledge as early as today
Create an account, invite the first person, and read what they know as soon as they have answered. The free trial package lets you try a first interview while the allocation lasts.
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