Research & Analysis Platforms
Build a multi-agent research discussion platform
Kliv is an AI app builder. Describe your multi-agent research discussion platform — document shelves, per-corpus agents, cited answers, findings, and reports — and it builds the real app.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a single chat tool or a document viewer — it’s an AI that builds software for you.
You describe the app you need in your own words, and Kliv builds it: document shelves, agents, question threads, citation views, findings, reports, roles, and screens. What you get is a real application that’s yours. You can use it, change it later by asking, and run it on your own domain. It isn’t a template with your name on it.
On this page, that app is a research room where several narrow agents answer from separate corpora. Kliv builds all kinds of web apps; this is one.
Why build your own research discussion platform?
Research teams often need to know which source said what. One assistant that blends everything together is the wrong fit when the value is provenance.
A battery teardown shop might keep patent filings, internal teardown notes, and supplier disclosures separate. Each source type should answer from its own shelf, and the human team should compare the answers.
Kliv builds that structure: one agent per document shelf, the same question sent to all of them, answers with citations, and findings that keep the thread behind the conclusion.
The room, the shelves, and the record
Five records turn a weekly research discussion into an archive.
Document shelves
Patent filings, teardown notes, supplier disclosures, or any other corpus can be uploaded and kept current as separate knowledge bases.
One agent per shelf
Each agent answers only from its own shelf. The patents agent has not read the teardown photos, so its answer means “the filings say this.”
Sessions and agendas
A weekly session can have questions queued in advance, each tied to the report or project it supports.
Threads and findings
A finding stores the question, each shelf’s answer, citations, and the human verdict, linked back to the full discussion.
The report pipeline
Findings can flow into draft sections, and draft sections into the published report that clients read.
An example: Katrien’s battery research desk
Here’s how one research business might use it. It’s only an example — you would describe your own documents, agents, questions, and reporting process.
A question is added to the agenda
The week’s reading flags a claim about a dry-electrode process. Ruben adds it as question four, tagged to the Q3 cathode report.
All shelves answer the same question
During the session, the question goes to the patents agent, teardown agent, and supplier-disclosures agent at the same time. Each answer cites the pages it used.
A disagreement becomes the useful result
The patents agent cites paragraph 0142 of a filing. The teardown agent points to March cell photos and a materials table that contradict it. Both citations can be checked.
Humans record the verdict
Katrien’s team decides the process is claimed but not yet shipped. The verdict is saved with attribution and date.
The report keeps the path back
The finding lands in a draft report with the threads attached, so a client challenge months later can be answered from the record.
Describe the research room you want
Kliv builds from your description, so the more detail you give, the closer the first version. Include each document shelf, who can ask questions, citation requirements, findings, and reporting. Here are three to build on:
Policy evidence desk
Separate evidence bodies, parallel answers, and staff verdicts.
“Build a policy research platform. Create separate shelves for trial registries, agency guidance, and our own briefs; give each shelf its own agent; let staff ask one question to all agents before drafting; require citations on every answer; and save a human verdict as a finding.”
Patent watch desk
Weekly filings, shelf-limited answers, and attorney review.
“Build a patent monitoring tool. New filings land on a patent shelf every week, an agent answers only from those filings, flagged claims route to an attorney review list, and each reviewed claim keeps citations and a status.”
Competitor filing digest
Per-company agents and a Monday memo workflow.
“Build a competitive intelligence platform. Feed earnings transcripts and annual reports into separate per-company shelves, give each company its own agent, compare answers on one screen, and turn approved findings into the Monday memo.”
What makes the room trustworthy
Each shelf is built from documents your team uploads. An agent reads its own shelf and nothing else. When a shelf has no support for an answer, the agent should say so.
Every exchange survives. Threads attach to findings, findings attach to reports, and the chain lives in your own database. If a client pushes back, the answer is traceable.
A multi-agent app is useful when provenance matters. Every answer names its shelf, and disagreement becomes data your team can judge. How Kliv builds AI apps explains the broader pattern.
Common questions
What exactly is Kliv?
Kliv is an AI that builds custom web apps from a description. You describe your research workflow, and Kliv builds the app you own.
Do I get a real app, or a template?
A real app. Kliv builds the document shelves, agents, question threads, citation views, findings, reports, and roles around your process.
Can I change it after it’s built?
Yes. You can add shelves, change findings, adjust roles, or add a report workflow by asking.
Do the agents debate each other?
No. Each agent answers the same question from its own shelf. Your team compares the answers and records the verdict.
Where do the documents live?
In your app’s file store, private by default, feeding separate knowledge bases per shelf.
Can one shelf use documents from another shelf?
Only if you design it that way. The default pattern is separation, so each answer clearly names its source base.
Could clients ask questions too?
Yes, if you choose. A client role could ask questions against published reports only, with each client’s questions kept separate.
What happens when an agent is wrong?
The answer carries citations, so you can check the pages. The human verdict layer exists so your team can overrule and record that decision.
Can findings feed reports?
Yes. Findings can become draft sections, with links back to the threads and citations behind them.
Can I use my own domain?
Yes. The platform can run on your own domain.
Can I move off Kliv later?
Yes. The code syncs to your own Git repository, and your records can be exported.
Do I need to run retrieval infrastructure?
No. You describe the shelves and upload the documents; the app handles the knowledge bases for those agents.
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Make every answer name its source
Describe your shelves, agents, questions, citations, findings, and report workflow in as much detail as you like. Kliv builds the research room around them.