Operations · Starter · updated 2026-10-23
Monthly KPI report with AI commentary
Query KPIs from BigQuery, have an LLM write commentary on what changed, build a Google Doc / PDF and send it by email and Teams.
1Is this my problem?
One consistent report beats ten dashboards nobody opens.
You'll recognise this if…
- Monthly report built by hand.
- Numbers differ between decks.
- Commentary written late.
2Is this solution worth it?
The sources describe how this is built but publish no hard results, so the figures below are our estimates.
Your ROI, with the assumptions shown
Prefilled with illustrative assumptions (3 h/week at $60/h, 70% automated, build $2,500). Change them to your numbers.
Limits and when not to build it
Skip it if: No central data.
- Agree metric definitions first.
3How does it work?
One small internal tool does this for you. The same job, before and after:
Before · by hand
- 1st of the month: someone notices
- Query BigQuery
- Write commentary (by hand)
- Build Doc / PDF
- Email + Teams
Monthly KPI report with AI commentaryIllustrative
- Starts automatically: 1st of the month
- Query BigQuery
- AI: Write commentary
- Build Doc / PDF
- Email + Teams
✦ AI step · ● human checkpoint · ✓ automatic
Explaining movements in plain words; numbers come straight from the query.
- Write commentary
Your tool connects to
Under the hood: flow, architecture and vendors
- When: 1st of the month
- Query BigQuery
- Write commentary
- Build Doc / PDF
- Email + Teams
Architecture
Vendors commonly used
Maturity ladder
What each level adds. Most teams start at level 1 or 2 and climb. Highlighted: where this build sits.
- Level 1Basic automation
Trigger: 1st of the month. Fixed rules then query bigquery, build doc / pdf, email + teams. No AI involved.
- Level 2AI-assisted
An LLM handles the judgement step (write commentary) and a person reviews every output before it is used.
- Level 3Autonomous agent
The agent runs end to end on its own and only stops for exceptions. Owner skims before send (optional).
- Level 4Self-learning system
Outcomes and human corrections are logged and fed back into prompts and rules on a schedule, so accuracy improves with use.
Seen in the wild
Links checked 2026-10-23. We describe these builds from public material; we are not affiliated with these companies.
4Who can build it?
Matched on services, platforms and industries agencies list on their own sites, and on their published projects.
GoodspeedLondon, United KingdomWhy matched: Reporting/dashboards; uses n8n, Claude.
Related project: AI Workflow Automation Built With n8n — Chuck Peters' community app needed to handle Grand Old Day, a 250,000-person street festival on a single avenue, with a hard launch date ten…
Published price: From $10,000
Connex DigitalUniversal City, United StatesWhy matched: Reporting/dashboards; uses n8n, Claude.
Related project: Actionstep Automation Services for Law Firms: 125-Firm Pilot — How one association piloted Actionstep automation services for law firms—5 templates, group training, and optional 1:1 support—to roll out t…
No published price
AutomateNexusSeattle, United StatesWhy matched: Reporting/dashboards; uses n8n, Claude.
Related project: Payroll Automation — A monthly process of more than thirty manual steps collapsed into an automated pipeline with accuracy checks built in.
Published price: From $3,500
Nex AutomationsAhmedabad, IndiaWhy matched: Reporting/dashboards; uses n8n, Claude.
Related project: Five-Stage AI Article Pipeline on Make.com, Airtable and OpenAI — How an editorial team that rejected one-shot AI writing now runs a five-stage pipeline with a human gate at every stage. Make.com, Airtable,…
Published price: From $5,000
Avalency StudioWhy matched: Reporting/dashboards; uses n8n, Claude.
Related project: How Avalency automated high-intent follow-up for Spectra Perfumes — See how Avalency built a behavior-based email automation system for Spectra Perfumes, covering key shopper journeys and reducing campaign se…
No published price
Alltomate by Miguel Carlos AraoWhy matched: Reporting/dashboards; uses n8n, Claude.
Related project: Lead Capture Automation Case Study: Dot-Med to Dynamics CRM — See how Alltomate automated Dot-Med inquiries into Microsoft Dynamics CRM, standardizing lead data and eliminating manual entry.
No published price
Projects, tools and prices come from each agency's own website (crawled October 2026). Not paid placements.
5What should I do next?
Questions
What does a "monthly kpi report with ai commentary" automation do?
Query KPIs from BigQuery, have an LLM write commentary on what changed, build a Google Doc / PDF and send it by email and Teams.
Which tools can I use to build it?
Common choices are n8n, BigQuery, Claude, Google Docs, Outlook, Microsoft Teams. Teams often use n8n, BigQuery, Claude together; the right mix depends on what you already pay for. n8n, Make and Zapier can all handle the workflow steps.
How much does it cost to build?
As a rough estimate, agencies often quote $1k–$3.5k for a first version of this workflow, plus monthly tool and AI usage fees. Your quote depends on how many systems are involved and how clean your data is.
How much time does it save?
Our estimate for a small team is about 2–4 hours a week. This is a rough guide, not a measured result; measure your own baseline before you start.
Where does AI actually help?
Explaining movements in plain words; numbers come straight from the query.
Who actually runs this?
Public examples include: n8n community template #16538: Generate monthly BigQuery KPI PDF reports with Claude.
Where should a person stay in the loop?
Owner skims before send (optional).
What usually goes wrong?
Agree metric definitions first.
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