Operations Teams
Work in progress, turnaround times, bottlenecks and capacity, visible without asking anyone.
One place that answers the questions currently scattered across five systems and a spreadsheet someone rebuilds every week. Defined once, trusted by finance, and fast enough to use live.
If someone rebuilds the same report every Monday, this replaces that.
Talk about your data →Work in progress, turnaround times, bottlenecks and capacity, visible without asking anyone.
Revenue, margin and pipeline on one page, with figures that reconcile to the ledger.
Client-facing reporting you can hand over, and in-product analytics your users actually open.
Live queues, throughput, SLA breaches and workload across teams and locations.
Recurring revenue, margin by product or client, cash position, month-to-date against plan.
Branded reporting your clients log into, with permissions that keep accounts separated.
The report finance insists on, generated on a schedule and delivered without a human rebuilding it.
Watch the numbers that must not drift quietly, and tell the right person when they do.
Analytics inside your own product for your users, built on your existing data model.
Projects, tasks and utilisation, joined across the tools your teams already use.
The unglamorous part that decides whether anyone trusts the dashboard in month three.
One written definition of every KPI, so no two charts can disagree in the same meeting.
They die of disuse: two numbers disagreed once, someone went back to their spreadsheet, and nobody ever opened it again. We build against that failure directly.
Discuss your reporting →Written down, in one place, so "a sale" means the same thing on every screen.
Three figures verified by hand against the system of record. Trust is earned before rollout.
A named first team, a 30-day review, and permission to delete anything nobody opens.
Typical ranges, not a quote. What actually moves the number is how many sources feed it, how bad the source data is, and how complex the permissions are. See pricing →
One data source, one team, one screen of the numbers that matter most. $2,500 – $5,000 · 2–3 weeks
Two to four sources, role-based access, filters, drill-downs and exports. $5,000 – $25,000 · 3–8 weeks
Many sources, a metrics layer, scheduled PDF reporting and client-facing portals. $25,000+ · 8–16 weeks
Analytics embedded in your own SaaS product for your users. From $8,000 · 4–10 weeks
An abandoned dashboard, audited and rebuilt around definitions people agree on. From $3,000 · 2–4 weeks
Find the systems, confirm what is genuinely queryable, and map which field means what.
One written definition per KPI, agreed with the people who will defend the numbers.
Start from the decisions, then choose the charts. Layout, filters, drill-downs and exports.
Ingestion, scheduled refresh, permissions, caching, plus hand-verification of three figures.
A named first team, training, and a 30-day review of what is actually being opened.
Add sources and screens once the first one is trusted, not before.
Typically $5,000 to $25,000 depending on the number of sources, permission complexity, and whether custom PDF reporting is required. A focused pilot on one source is usually $2,500–$5,000.
Yes — REST or GraphQL APIs, or reading directly from PostgreSQL, MySQL or SQL Server, then normalising the data so the definitions agree across systems.
Usually scheduled: hourly for operations, daily for finance and executive reporting. True real-time is rarely worth the cost unless you are watching something genuinely time-sensitive.
It almost always is. We budget a cleaning phase at the start and build validation into the pipeline, so the same problem cannot silently return next quarter.
Reconcile before launch: pick three figures and verify them by hand against the system of record, then add automated checks that flag implausible movements.
Because the metrics were never defined in one place, the numbers disagreed once, and everyone quietly went back to spreadsheets. That is what the metrics layer and the 30-day review exist to prevent.