Business Tools
Build a help center and knowledge base
Kliv is an AI app builder. Describe a help center and knowledge base where articles, manuals, search, agent answers, escalation, support threads, and customer records work from one corpus.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a hosted help-desk template you sign up for and configure — it’s an AI app builder that creates custom software for you.
You describe what you need in plain words, and Kliv builds the real app: the data, the logic, the screens, and the workflows. You own the result, you can change it later by asking, and you run it on your own domain and your own accounts. It isn’t a template with your name on it.
On this page, that app is a help center and knowledge base with articles, search, agent answers, support threads, customer records, and staff workflows. Kliv builds all kinds of web apps; this page focuses on one useful shape.
Why build your own help center
A product company often already has the answers: manuals, error-code guides, how-tos, warranty records, and experienced support staff. The problem is that the material is scattered and customers still ask the same questions.
Kliv builds the help center as your own app. Articles are records in your database. The search box, the agent, and support threads read the same corpus, so fixing one article fixes every path to the answer.
What the help center is made of
Six parts built around one knowledge base.
Article corpus
Manuals, guides, and how-tos become living articles, indexed when saved.
Error codes and products
An error code stores code, affected machine versions, cause, fix, and linked article so the agent can cite the right record.
Agent up front
The agent answers from your own corpus and, for signed-in customers, from their own machines and warranty dates.
Semantic search
A search like “machine is leaking underneath” can find the drip-tray seal article even when the exact words differ.
Support threads
When the agent hands off, a thread opens with the conversation attached so the customer does not repeat the issue.
Customer shelf
Signed-in customers can see their registered machines, warranty status, and past support threads, scoped to their own rows.
What one corpus makes possible
Auditable deflection
Every agent conversation can be stored as a transcript in your database, so you can read what customers actually asked.
Pages crawlers can read
Articles are prerendered for search engines and AI crawlers, so your fix can be cited instead of a forum guess.
Analytics on gaps
You can track searches that end without a click and use that event to decide which article to write next.
Replies with context
Support replies use your templates, and the whole exchange stays on the customer record for the next staff member.
An example: Rosa’s espresso machine company
Here’s how one product company might use it. It’s only an example — you would describe your own products, articles, customer records, escalation rules, and support workflow.
Old manuals become articles
Rosa imports nine years of manuals and error-code guides. Staff turn the most-used sections into articles organized by machine version and topic.
Search finds the likely fix
A customer searches “leaking underneath.” The help center finds the drip-tray seal article even though the customer did not know the part name.
The agent answers from the company corpus
The assistant explains E-42 using Rosa’s error-code guide and cites the matching article instead of inventing an answer.
A signed-in customer gets a specific answer
When a customer signs in, the agent can see that customer’s registered machine and warranty date, not anyone else’s records.
Escalation keeps the transcript
If the question needs a human, a support thread opens with the conversation attached, assignment, status, and the customer record.
Describe what you want to build
Kliv builds from your description, so the more detail you give, the closer the first version. Include article sources, search behavior, agent boundaries, customer records, and escalation rules. Here are three to build on:
Product help center
Manuals, error codes, and escalation.
“Build a help center for our appliance brand. Import manuals and error-code guides, organize articles by product line and machine version, add an error-code lookup, let an assistant answer only from our documents, and hand off to email support with the chat history attached.”
Internal IT knowledge base
Staff how-tos and tickets.
“Build an internal IT knowledge base for our 240-person company. Store staff how-tos by system, index them for semantic search, let an assistant answer from approved articles only, and turn unanswered questions into tickets assigned to the IT team.”
Software docs portal
Versioned articles and cited answers.
“Build a documentation portal for our SaaS app. Store versioned articles for v1, v2, and beta features, add semantic search, and add an assistant that cites the exact page and version behind each answer.”
How it comes together
One corpus, three paths. Search, the assistant, and the error-code lookup read the same records. Updating an article updates every path.
The agent knows who is asking when they sign in. It can read the customer’s own machine and warranty rows under the same access rules as the rest of the app. Anonymous visitors get public articles only.
Escalation is part of the app. Support threads store assignment, status, customer, and the attached agent transcript.
The help center stays yours. Articles are your rows, the source code syncs to a Git repository you control, and your customers’ questions stay in your app.
The agent is central to this build. Grounding, capabilities, and transcripts are explained on the agents product page.
Common questions
What exactly is Kliv?
Kliv is an AI app builder. You describe the help center and knowledge base you need, Kliv builds it, and you own the result.
Do I get a real app, or a template?
A real app. Kliv builds the database, the logic, and the screens for your specific case — not a theme or preset workflow you fill in.
Can I change it after it’s built?
Yes. You ask for changes in plain words, and Kliv updates the app without making you start over.
Can I use my own domain?
Yes. Public help articles and support pages can run on your own domain.
Where do the agent’s answers come from?
From the knowledge base you author: manuals, guides, articles, error-code records, and customer rows the signed-in user is allowed to access.
Can customers always reach a human?
Yes. Escalation can open a support thread with the agent conversation attached, and customers can open a thread directly.
How do years of manuals get in?
You can upload existing documents, index them for search, and turn the most useful sections into articles over time.
What does it cost as the team grows?
Kliv does not price by support-seat count inside your app. Support staff are users with roles.
Will articles show up in search?
Yes. Public articles are prerendered for crawlers, and the sitemap updates as pages change.
Can signed-in customers get specific answers?
Yes. The agent can use their own registered products, warranty dates, and past threads while keeping other customers’ rows private.
Do I need a separate help-desk tool?
No, if you want support threads built into the app. Threads can store assignment, status, replies, and the agent transcript.
Can I move off Kliv later?
Yes. Your source code syncs to your own Git repository, and your articles and support records are yours.
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Answer from your own knowledge
Describe your documents, products, article structure, agent boundaries, customer records, and escalation workflow. Kliv builds the help center and knowledge base around them.