Browse categories
Explore
Fiverr Pro
English
$
USD
I will google workplace automation ai studio knowledge capture n8n gemini claude cowork
AI system Engineer, The Expert for your Automation needs
Real estate agencies, medspas, hotels, and service businesses routinely lose bookings and qualified leads to slow response times and disconnected systems. Properly engineered AI automation closes thos...
About this Gig
I will build a closed-loop Google Workspace automation system that captures your team's daily communication.
WHAT YOU GET:
- Automated ingestion from one or more Workspace channels (Meet, Gmail, Chat)
- Multi-step LLM classification and routing
- Human-In-The-Loop AI routing
- Structured entry formatting that matches your existing doc templates
- Workspace-native AI pipeline
- Service account with domain-wide delegation configured securely
- Full documentation handoff so your team maintains it internally
WHY ME:
I build prompt pipelines, not just no-code tool assembly. I architect for the exact "keep it inside Workspace" preference while flagging where an external orchestrator like n8n is the smarter call, and I explain why in plain terms.
Every delivery includes architecture docs, runbooks, and a phased pilot plan so you're not locked into a black box.
Message me and I'll map your single-channel pilot today.
BUILT WITH: n8n, Google Workspace Studio, APIs (Drive, Docs, Gmail, Chat, Meet), Gemini or Claude, Google Cloud service accounts, Claude Code, NotebookLM, Agent2Agent (A2A), Zapier, n8n, AI Agent Orchestration, Agentspace, Google Chat Bot, livekit, telnyx, twilio
Purpose:
Business
FAQ
Which channel should we start with :: Meet, Gmail, or Chat?
Start with Meet transcripts if your highest-value decisions happen in calls. Start with Gmail if you need to filter for decision-containing threads first. Chat works best when you designate specific spaces for actionable discussion. I recommend Meet for the pilot because transcripts have clear bound
Can you keep everything inside Google Workspace without external tools?
Partially. Gemini can process content natively, and Drive API handles the writes. But for multi-step routing, conditional logic, and human review queues, n8n or Google Workspace Studio provides the orchestration layer that native Workspace alone cannot yet match. I architect hybrid solutions.
How does the human review queue work?
When the LLM confidence score falls below your threshold — or when content is ambiguous, multi-topic, or references sensitive decisions — the entry routes to a designated Google Chat space or email instead of auto-appending. Your reviewer approves, edits, or rejects with one click. The queue depth,
Do you work with Claude Projects, or only Gemini?
Both. If your current AI layer is Claude Projects fed by Google Docs, the automation keeps feeding those same docs — nothing changes for your agents. If you're evaluating a Gemini migration, I design the prompt pipeline to be model-agnostic so switching requires only an API key swap, not a rebuild.
What happens if the same topic appears in Meet and then in Chat?
Deduplication is built into the Standard and Premium tiers. The pipeline checks for semantic similarity against recent entries before appending. If overlap exceeds your threshold, it updates the existing entry rather than creating a duplicate. This keeps your rollup docs clean and prevents
Can this be adapted for industries outside marketing agencies?
Yes. The same architecture serves legal firms (case notes to matter files), healthcare practices (consultation summaries to patient records), consulting teams (client calls to project docs), and real estate agencies (listing calls to deal files). The core pattern — communication capture, AI class
What documentation do you hand off?
Every build includes: architecture diagram, n8n workflow JSON with annotated nodes, Google Cloud Console setup guide, service account and domain-wide delegation configuration steps, prompt library with version history, runbook for common failures and recovery, and a 30-minute walkthrough call.
How do you handle Google Workspace API quotas and costs?
I design for quota efficiency: batch reads where possible, incremental updates instead of full doc rewrites, and careful trigger filtering so only actionable content enters the pipeline. For high-volume teams, I implement rate-limiting and backoff logic. Typical agency volume stays well within.
Does this integrate with emerging platforms like Google Workspace Studio or A2A?
Google Workspace Studio is monitored as a native orchestration alternative to n8n; I can pivot the architecture if it matures. The Agent2Agent (A2A) protocol is emerging for cross-platform agent interoperability — your pipeline is designed with standard API patterns that will adapt cleanly.
What does the phased pilot plan look like?
You approve each phase before the next begins. No full-commitment upfront, the pilot validates the approach with real data from your team.
