Monitors Google Drive for new or updated documents, creates embeddings and stores them in Pinecone, answers queries via GPT-4o, logs Q&A to Sheets, and notifies teams with a weekly digest to keep knowledge current.
This AI agent reads every Google Doc from a designated Knowledge Base folder, converts the content into context-rich chunks, and creates 1536-dimension embeddings. It stores the embeddings in Pinecone with document metadata for fast semantic search. When a question is asked through a webhook, the agent retrieves relevant chunks, queries GPT-4o to answer strictly from the provided documents, and logs the Q&A with source and confidence. It also ingests new or updated documents weekly and sends a digest highlighting changes.
Concrete actions the agent performs to automate knowledge capture and retrieval.
Ingests all Google Docs from the Knowledge Base folder into the AI knowledge base.
Splits each document into semantic chunks with overlap to preserve context.
Converts each chunk into 1536-dimension embeddings using OpenAI text-embedding-3-small.
Stores embeddings in Pinecone with document metadata for fast search.
Accepts questions via webhook from Slack, a form, or internal tools.
Logs every question, answer, source, and confidence score to Google Sheets.
before → поисковая dysfunction within Drive where employees waste time locating or guessing which doc contains the needed policy or product info. before → information silos slow onboarding, cause inconsistent answers, and create compliance risks. before → manual searching across scattered files leads to missed updates and stale knowledge. before → no audit trail makes it hard to verify what was used to answer a question. before → weekly digest is manual, so teams miss critical changes. after → answers come from a single, source-verified KB with citations. after → onboarding accelerates with up-to-date, policy-backed content. after → employees get fast, accurate responses with source links. after → every Q&A is logged for governance. after → teams receive a clear weekly digest of current content.
A simple 3-step flow that non-technicals can follow.
Reads all Google Docs from the Knowledge Base folder, splits content into 500-character chunks with 100-character overlap, embeds each chunk using OpenAI text-embedding-3-small, and stores embeddings in Pinecone with the document name as metadata.
Converts the incoming question to an embedding, retrieves the top 5 semantically similar chunks from Pinecone (cosine similarity), filters out chunks below a 0.3 score, and prompts GPT-4o to answer only from the retrieved content with source citations.
Every Sunday, checks Drive for new or updated docs, re-ingests changed files, and sends a digest email highlighting what’s current, new, or updated.
A realistic scenario showing task, time, and outcome.
Scenario: A product manager asks via the internal API, “What is the current enterprise discount policy?” at 9:12 AM on Monday. The agent processes the request, searches the Knowledge Base for the latest pricing docs, and returns a precise policy snippet with the source paragraph and a confidence score. The user receives a clear answer within 3 seconds, including a link to the source document for verification.
Roles that gain fast, reliable access to policy and product information.
Need instant access to company policies and product docs to answer investor or partner questions.
Reduce time spent answering routine policy questions and onboarding queries.
Get up-to-date product and pricing information to respond to prospects quickly.
Build client-facing AI knowledge tools and automations for clients.
Reference product FAQs and release notes to inform decisions.
Improve internal support by quickly verifying guidance from official docs.
Tools used and what the AI agent does inside each tool.
Ingests and monitors the Knowledge Base folder for new/updated docs.
Generates 1536-dim embeddings and runs GPT-4o to answer with citations from the KB.
Stores embeddings and performs fast semantic search to surface relevant chunks.
Logs Document Registry and Q&A Log for auditing and change tracking.
Sends weekly KB digest to stakeholders.
Receives questions via webhook and routes them to the Q&A agent.
Concrete scenarios where the KB AI agent shines.
Practical questions about data, usage, and setup.
Data stays under your Google and OpenAI access controls. Access to the knowledge base is governed by your Google Drive permissions, and embeddings/queries are processed using your OpenAI keys where configured. The system stores metadata in Pinecone and logs in Google Sheets; none of the data is exposed outside your environment unless you authorize it. You control who can trigger ingestion, Q&A, and digest emails. Regular audits can verify what content was used to answer any given question.
Yes. The current setup uses OpenAI text-embedding-3-small for embeddings and GPT-4o for answering. You can adjust the embedding model and the no-hallucination prompt to better fit your content and accuracy requirements, and you can tailor the citation format. Any changes should be tested in a staging workspace before production. Note that changes may affect performance and cost, so plan accordingly.
If the knowledge base doesn’t contain relevant material, the agent clearly states that the answer isn’t available and does not guess. It can suggest checking the latest docs or provide a plan to retrieve supporting content. This behavior helps maintain trust and reduces risky or inaccurate responses.
The system performs automatic ingestion every Sunday to capture new or updated documents. If a file changes, it is re-ingested automatically during the maintenance step. This schedule keeps the KB fresh without requiring manual monitoring.
Yes. The agent accepts questions via a webhook, which can be triggered from Slack, Forms, or other internal tools. You can surface answers in your preferred channel, with citations, and maintain an auditable log in Sheets. Additional integrations can be added to push digests or alerts to collaboration platforms.
Yes. Every Q&A is logged to Google Sheets with the question, answer, source, and confidence score. This audit trail supports governance, compliance, and easier reviews. You can export logs for external audits or internal reviews.
You can trigger the ingestion step manually during setup to populate the KB, then issue test queries through the webhook to verify relevance and citations. Review the Q&A logs to confirm accuracy and source attribution. Use the weekly digest to confirm that new content is detected and surfaced correctly.
Monitors Google Drive for new or updated documents, creates embeddings and stores them in Pinecone, answers queries via GPT-4o, logs Q&A to Sheets, and notifies teams with a weekly digest to keep knowledge current.
