Knowledge Base
Knowledge Base Template โ SaaS Product
Features catalog, pricing, integrations, objection bank, competitor comparison.
SaaS knowledge base structure for customer support agent. Deploy-ready.
๐ What's inside the download
โจ What you get
- โStructured YAML + JSON schemas for direct ingestion
- โ20โ30 FAQ templates calibrated for the industry
- โDocument hierarchy + tagging system
- โReady for Pinecone, Weaviate, LangChain, LlamaIndex, Supabase pgvector
- โChunking + embedding recommendations
- โExample: 5 real entries filled in so you can see the pattern
๐ Sneak peek โ first page
Actual content from the file
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AI AGENT KIT โ KNOWLEDGE BASE SAAS PRODUCT
Sales & Support Concierge Agent โ Ready-to-Deploy Bundle v1.0
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0. KIT OVERVIEW
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This kit is a complete, drop-in package for deploying a conversational AI agent that represents a Knowledge Base SaaS product (hereafter "HelixKB" โ replace with your brand). The agent is designed to operate across web chat, in-app widget, Slack, Intercom, and voice channels. It handles three core jobs: (1) qualify and educate prospective buyers, (2) surface pricing and integration information with accuracy, and (3) deflect common objections and competitor comparisons toward a booked demo or self-serve trial signup.
Every asset below is copy-paste ready. Variables are wrapped in {{double_braces}}. Guardrails are enforced via the system prompt and validated with the included transcripts. No external orchestration framework is required โ the kit runs on any LLM that supports system prompts and tool use (Claude, GPT, Gemini, local Llama variants with function calling).
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1. SYSTEM PROMPT BLOCK
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Copy the entire block below into your agent's system prompt field. Do not edit sections marked [LOCKED].
----- BEGIN SYSTEM PROMPT -----
You are H
โฆ full download is a formatted PDF with 3,000โ5,000 words ยท complete guide
๐ฏ Who this is for
- โAgent builders who need a KB scaffold, not a blank YAML
- โCompanies onboarding their first RAG pipeline
- โFreelancers building client KBs and tired of starting from zero
โ Frequently asked
What format is this in?
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Structured plain text with YAML and JSON blocks clearly separated. Copy into your vector DB ingestion pipeline directly.
Which embedding model should I use?
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Recommendations included: OpenAI text-embedding-3-small for cost, Cohere embed-multilingual-v3 for Hindi content, BGE-large for self-hosted.
Can I add my own data on top?
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Yes โ the schema is designed to be extended. Add your products, policies, hours without changing the base structure.