OpsQuanta

Project Overview

OpsQuanta is a 25-person post-Series A B2B SaaS company building operations analytics for mid-market logistics companies. Their head of ops was spending most of a working day every week pulling Monday board prep — Stripe metrics, GA4 traffic, HubSpot pipeline movements, support ticket volume — assembling it into a slide deck nobody read carefully because it landed too late.

NodeSparks built a custom AI agent that drops a board-ready digest into Slack on Sunday night, automatically. Same numbers, computed deltas vs last week, three highlighted talking points the founder actually opens the meeting with. The Monday afternoon ritual disappeared.

The Problem

OpsQuanta's ops lead had inherited a Monday board ritual that compounded as the company grew. Six data sources, three different export formats, manual reconciliation in a spreadsheet, then a deck. Average prep time: 4 hours per week. Average usefulness by the time the deck shipped: low — the numbers were already 36 hours old when the board opened them.

They had tried Geckoboard ($95/mo) for live dashboards and Hex ($150/mo) for the deeper SQL queries. Both worked, neither replaced the ritual. Geckoboard's dashboards were always-on but no one had time to summarize what changed. Hex required someone fluent in SQL to maintain notebooks. Annual cost of the stack: $2,940. Time saved: marginal.

The Build

We scoped the build over a 90-minute discovery call. The deliverable was a single agent that runs every Sunday at 21:00 UTC, pulls from Stripe + GA4 + HubSpot + Plain (their support tool), computes the eight metrics the founder actually cared about, calculates deltas against the prior 7 days, and posts a Slack message in the format the board already expected.

The agent was built on Claude Code as the orchestration runtime, with native API clients for each data source rather than going through Zapier. Total build time: 9 days. Test runs against real data started on day 5. Production cutover happened on a Sunday — the next Monday board prep was zero work.

Stack

• Runtime: Claude Code (Anthropic) for orchestration and the natural-language summary step
• Data sources: Stripe API, GA4 Data API, HubSpot Reporting API, Plain API
• Schedule: GitHub Actions cron + a small TypeScript wrapper
• Output: Slack incoming webhook to the #leadership channel
• Hosting: client's own GitHub repo, runs free on GitHub Actions minutes

Outcome

• Board prep time: ~4 hrs/wk → 0 hrs/wk (agent runs unattended)
• Killed Geckoboard ($95/mo) and Hex ($150/mo) — $2,940/yr saved on tools
• API costs (Anthropic + data source calls): ~$67/mo
• Net cash savings year 1: $2,140 + recovered ops time worth ~$13k at fully-loaded cost
• Payback period on the $7,500 build: ~5 months on tool savings alone

Six months in, the ops lead has extended the agent twice (added churn cohort analysis, added a cash-runway alert) without our involvement — the code is in their repo and the patterns are clear enough that their in-house developer picked it up.