Insulin · Knowledge Bases New

An AI knowledge base that answers from your documents.

Load the playbooks, policies, and runbooks your marketplace business already runs on. Insulin agents search them before answering and return the sources they used — so you can check the answer, not just take it.

Now in early access — request a demo to get started.

Insulin · Knowledge Bases
Deal Desk Policy
31 documents
Listing Playbook
42 documents
Finance Runbooks
18 documents
Co-Sell Program
24 documents
+ New base
What discount needs VP approval?
Anything above 25% off list requires VP of Sales sign-off before the private offer is issued.
Sources
Discount Approval Matrix.pdf p. 4
Deal Desk Runbook.md § 2.1
Grounded in Deal Desk Policy

Definition

What is an AI knowledge base?

An AI knowledge base is a searchable repository of proprietary documents that an AI agent consults before it answers. In Suger Insulin, a knowledge base is how you make sure an agent replies from your own material rather than from a model's general training.

That distinction matters more in marketplace operations than almost anywhere else. The rules that govern a private offer, a listing submission, or a co-sell referral are specific to your company and your agreements. A model that has never seen them can only approximate. An agent with a knowledge base attached reads the actual policy and shows you which document it came from.

Hybrid search finds the passage

The agent searches your knowledge base before it answers, combining keyword and semantic matching so the right passage surfaces whether you used the internal jargon or not.

Cited sources come back with it

Responses carry the documents they were drawn from, so a reader can check the claim instead of trusting it. That is the difference between an answer and a guess.

Your documents stay yours

A knowledge base holds your proprietary material, and an agent only reaches the bases you attach to it — scope is the boundary, the same way integration access is.

What to load

The documents your business already runs on

You do not need to write anything new. Most teams start by loading material that already exists and is already authoritative — it is simply scattered across drives, wikis, and inboxes today.

  • Listing playbooks How your team gets a product live on each marketplace, and what tends to go wrong.
  • Pricing and packaging policy The dimensions, tiers, and discount rules a deal desk answer has to respect.
  • Private offer approval rules Who signs off on what, at which threshold, and in which order.
  • Co-sell program requirements What each hyperscaler expects on a referral before it will be accepted.
  • Contract and legal templates The clauses your team is allowed to agree to without escalation.
  • Internal runbooks Reconciliation, metering, and support procedures that currently live in one person's head.
Deal Desk Policy
Documents + Add
Discount Approval Matrix.pdf Indexed
Private Offer Checklist.docx Indexed
Deal Desk Runbook.md Indexed
FY26 Pricing Policy.pdf Indexing…
Attached to agents
Deal Desk Marketplace Ops

What changes

Institutional knowledge stops being a person

In most marketplace teams, the answer to "can we discount this?" lives with whoever has been there longest. A knowledge base moves that answer into a document every agent reads and every person can check.

  • New hires get the same answer a veteran would
  • Policy lives in a document, not in tribal memory
  • Every answer can be traced to a source
  • Update the document, and the answers update
  • Scheduled runs follow the same rules as people
  • Agents stay inside the bases you attach

How it works

From scattered documents to grounded answers

Start with one domain and one agent. A single well-grounded specialist is worth more than six that guess.

1

Create the base

Open Insulin in the Suger console and create a knowledge base for one domain — listings, deal desk, finance.

2

Add your documents

Load the proprietary material that already governs the work: playbooks, policies, templates, runbooks.

3

Attach it to an agent

Give the specialist that owns the domain access, so its answers are grounded from the first question.

4

Check the citations

Ask a question you already know the answer to, read the cited sources, and fix the document if the citation is wrong.

Knowledge Bases are part of Suger Insulin, the AI workspace in the Suger console — view pricing or contact sales for availability.

A knowledge base needs something to ground. Start with AI agents for cloud marketplace operations, put them on a timer with scheduled AI jobs, or install a ready-made specialist from the AI agent marketplace.

Want the grounded answer in a shared thread? Insulin channels put teammates and agents in the same conversation.

Frequently Asked Questions

Common questions about Insulin knowledge bases

What is an AI knowledge base?

An AI knowledge base is a searchable repository of your own documents that an AI agent consults before answering. It grounds responses in your company's proprietary information instead of the model's general training.

How do knowledge bases work in Suger Insulin?

You create a knowledge base, add your documents, then attach it to an agent. When that agent answers a question, it searches the base first and returns cited sources alongside the response.

What should we put in a knowledge base?

The material that already governs the work — listing playbooks, pricing and approval policy, co-sell program requirements, contract templates, and internal runbooks. Anything a new hire would otherwise have to ask someone about.

How is this different from a wiki?

A wiki waits for someone to search it. A knowledge base is read by the agent on every question, including inside unattended jobs, so the policy is applied rather than merely available.

Can we control which agents see which documents?

Yes. An agent only reaches the knowledge bases you attach to it, so you can keep finance material with the finance agent and deal desk material with the deal desk agent.

Ground your AI in your own documents

See how Insulin knowledge bases turn scattered playbooks into answers your team can verify.