A custom multi-source dashboard pulling daily revenue, traffic, anomalies, and action items from every tool you run on — with an AI-generated plain-English summary in your inbox at 6am. Built in 4–6 weeks for owner-operators who are tired of starting every day with an hour of mental arithmetic.
If your morning starts by logging into Square (or Toast, or Vagaro), then your booking software, then Google Ads, then Mailchimp, then your bookkeeper's spreadsheet — and assembling a mental picture by 10am that's already stale — this is the build that gives you 60 seconds in the morning instead of 60 minutes.
Med spas, salons, fitness studios, restaurants, dental groups, retail. Anywhere you're trying to compare locations and the answer is "go pull each one's report and add them up in your head."
Past the startup stage. You have real data flowing through real software. The patchwork of SaaS tools that got you here is now the bottleneck, not the asset.
Every morning someone exports CSVs and assembles a "morning report." That person is either you or a manager whose time you're paying for. Either way, the cost compounds week over week.
The operational picture you need to run the business sits inside 5–8 different tools, none of which talk to each other. By the time you've assembled it manually, half the morning is gone and you're reacting to fires instead of running the business. The cost shows up in three places.
That's 2.5–5 hours a week. 130–260 hours a year. Four to six weeks of full-time work, gone — for a picture that's outdated by lunch.
The Tuesday revenue dip you spot Friday. The Yelp review that should have triggered a response 48 hours ago. The location that quietly underperforms for three weeks before it shows up.
Pricing changes without margin data. Marketing spend without channel attribution. Hiring decisions without staff-utilization data. Everything's somewhere — but not somewhere actionable.
Operations Cockpit is a real engineering build — a Next.js application running on production infrastructure, with proper auth, audit logging, and the unglamorous engineering that separates a working production system from a Tableau view that breaks every time a vendor changes an API.
OAuth or API integrations to your specific tools — Square, Toast, Vagaro, Mindbody, ServiceTitan, QuickBooks, Stripe, Google Ads, Meta, Mailchimp, Klaviyo, Google Business, etc. Connector list is fixed in the SOW; additions are change orders. No surprises mid-build.
Revenue, traffic, conversion, retention, marketing spend, and operational KPIs in one dashboard. Per-location breakdowns where applicable. Date-range comparisons. Drill-downs into the underlying data.
An LLM-generated plain-English briefing in your inbox every morning at the time you want it: what changed yesterday, what's anomalous, what needs your attention. A 60-second read, with links back into the dashboard for any item you want to dig into.
Statistical baselines on the metrics that matter to you. When something deviates, it's flagged — not buried in a chart. Action items surface as a queue, not as charts you have to interpret.
Different views for owner, GM, location managers, marketing lead. Role-based access so each role sees the right data. Audit logging on every access for the regulated cases.
Designed mobile-first. The morning briefing should be readable on your phone before you've left the house — not a desktop-only experience that punishes you for being out in the field.
Multi-tenant Postgres with row-level security. Sentry + Better Stack observability. Cost-tracking middleware on every LLM call. Multi-LLM provider routing with fallback. The infrastructure that keeps the dashboard running when a vendor breaks an API at 3am.
A lot of people will sell you a "dashboard." Most of them break the second a vendor changes an API or your data gets remotely interesting. Three things make this build different.
Every integration is wrapped in our connector framework — normalized data models, retry logic, schema versioning, error queues. When a vendor breaks an API, we know within minutes and your dashboard keeps working off cached data while we patch.
Every model call goes through cost-tracking middleware. You see token spend per feature, per location, per user. Daily summary using the cheapest model that meets the bar — typically Haiku or Mini. Frontier models only when an eval proves they're necessary.
The AI-generated summary has a regression eval against historical days. We catch quality drift before you do — and we catch it before you start ignoring the briefing because it stopped being useful.
Standard Custom Tier engagement format. The paid scoping engagement produces the architecture, the integration list, and a fixed quote. Most engagements that proceed do so on the strength of the scoping output alone.
We map your current daily reporting workflow — every tool you log into, every spreadsheet you touch, every report you pull manually. By end of call we know whether Operations Cockpit is the right answer for you.
3–6 stakeholder interviews. System audit of your existing tools and data quality. Technical architecture sketch. Integration list locked. Fixed-quote SOW. Output is yours regardless of next step. Credits 100% if you proceed within 60 days.
Week 1: foundation (auth, schema, deployment pipeline). Weeks 2–3: connector layer for your specific tools. Weeks 4–5: dashboard, anomaly detection, AI summary. Week 6: polish, eval suite, pre-launch testing with your team.
Daily check-ins for the first week, weekly for weeks 2–4. Quarterly business review thereafter — surfaces follow-on builds when your business changes. Maintenance retainer covers hosting, monitoring, bug fixes, minor enhancements, and an LLM API baseline.
Most modern SaaS with a public API: Square, Toast, Vagaro, Mindbody, ServiceTitan, Booker, Acuity, Jobber, Lightspeed, Shopify, QuickBooks, Xero, Stripe, Google Ads, Meta Ads, TikTok, Mailchimp, Klaviyo, Google Business, Yelp, and many more. The exact list goes into your SOW. Legacy tools without APIs may need a Computer-Use Agent build instead — we'll tell you on the discovery call.
Our connector framework wraps each integration with retry logic, schema versioning, and an error queue. When something breaks, we get an alert within minutes. Your dashboard keeps working off cached data while we patch — typically same-day. This is the unglamorous engineering most templated solutions skip.
BI tools assume your data is already in a warehouse. Operations Cockpit does the connector work, the unification, and the AI layer that BI tools don't ship with. If you already have a Snowflake or Databricks warehouse with clean data flowing in, BI is the right answer — and we'll tell you that on the discovery call instead of selling you a build.
You own the deployment, the data, and the configurations. The platform components we use across multiple clients (the connector framework, auth wrapper, observability stack) remain ours — that's what makes the build economics work for both of us. Standard MSA terms; we'll walk you through the IP language during scoping.
Hosting and infrastructure (pass-through with margin), monitoring and uptime, bug fixes, minor enhancements (within a defined SLA), quarterly review, and the LLM API costs up to a baseline. New features beyond minor enhancements go through change orders so you stay in control of scope.
Yes — and most clients do. Common expansions: adding a location, adding a new tool to the connector list, adding a new role/view, layering in churn prediction or pricing optimization on top of the same data layer. Quarterly business reviews are where these get scoped.
Operations Cockpit is the spine of an "operational intelligence" stack. Three services pair naturally on top of it once your data layer is unified.
Marketing-channel attribution overlaid on your unified revenue data. Once Operations Cockpit's connectors are in place, this becomes a fraction of the original build effort.
Discuss →ML model trained on the customer data already flowing into your cockpit. Identifies high-risk customers 30–60 days before churn and triggers reactivation.
Discuss →Tool-augmented AI assistant that answers plain-English questions against the data layer. "What was my Tuesday revenue split by location?" — answered in seconds, not minutes.
See full details →A 30-minute discovery call confirms whether Operations Cockpit fits your operation, what the integration list would look like, and what the next step is. No paid commitment until we both agree it's the right build.