Trie is a growth product studio for SMBs. We help you prove demand, then design and build what you are launching, from apps and growth systems to physical prototypes.

What is Trie Microphone?

Trie Microphone is an iOS and web app from Trie, a growth product studio for SMBs. Record a voice memo about a business idea, and Microphone turns it into hypotheses, ad creative, and live paid-media experiments—so you get real click-through data before you build or scale spend.

SMBs with an idea worth testing and the ambition to ship it, with studio help across validation, design, and growth.

Do I own my data and my IP?

Yes. Your ideas, voice memos, and everything Trie produces stay yours. We never train models on your data, and we never resell or package it.

How do I get started with Trie?

Book a studio consult for GTM validation, design engineering, or growth marketing, or join the Trie Microphone waitlist on the homepage.

AI Deliverables · Jun 13, 2026 · 15 min read

How to Build a Company Knowledge Base for AI Deliverables

Name: Trie Microphone
Author: Trie

Structure proof, voice, and guardrails so AI proposals and decks pull from one source of truth—not stale prompts.

Build a company knowledge base for AI deliverables by organizing approved proof by segment, publishing voice do/don’t rules, storing pricing and capability guardrails, tagging content by use case (deck, proposal, memo), and maintaining it like a product—with owners, refresh cadence, and engagement-specific overlays.

Key takeaways

1. Knowledge bases for AI must be retrieval-ready—not document dumps.

2. Segment proof by industry and buyer role for relevant generation.

3. Voice rules prevent generic AI tone at scale.

4. Assign owners and refresh schedules like any revenue-critical system.

5. Engagement notes layer on top of canonical company content.

Most “knowledge bases” fail AI workflows because they are archives, not reservoirs. Files exist; retrieval does not. AI fills gaps—and hallucinates.

Layers of a deliverable-ready knowledge base

Canonical company layer

Positioning, approved metrics, case studies, pricing frames, legal guardrails, competitive counters.

Segment layer

Industry-specific proof, objection handling, and example outcomes tagged by ICP.

Engagement layer

Account notes, call summaries, and pursuit-specific constraints—never mixed into canonical without review.

Maintenance cadence

Weekly: call insights and new proof from wins. Monthly: battlecard updates. Quarterly: positioning and voice. Immediate: pricing or product launches.

Frequently asked questions

How is this different from Notion or Confluence?

Same content can live there—but AI deliverables need structured tags, approved status, and retrieval scoped to generation tasks.

Who owns the knowledge base?

RevOps or marketing ops often owns canonical layer; deal owners own engagement overlays.

How much content do I need to start?

Start with ten approved proof points, voice rules, and three case studies—expand from every shipped deck.

Trie is built for teams that ship client-facing deliverables at scale. Trie company brain is structured for retrieval into decks and proposals—not static wiki storage. If you are tired of re-prompting from zero and pasting into slides at midnight, start with a workflow that keeps company context, review, and presentation output in one place.

Related topics worth exploring next: company brain to pitch deck context, context graphs for sales teams, reduce AI hallucinations in proposals. Each connects to the same core challenge—turning AI speed into client-ready quality without losing brand, facts, or judgment.