One place to see how the business is actually doing. Live metrics, automated reports, and dashboards your team opens because they trust the numbers. No more Monday-morning stat wrangling.
We do not sell you a BI seat and walk away. We wire your systems, model your data, design the dashboards, and stay on it while your business changes. The output is dashboards your team actually opens.
The number you check before your morning coffee. Pipeline, revenue, cash, churn, headcount, and whatever else your board asks about. One glance, no filtering, always current.
The screens your ops, support, and delivery leads live in. Queue depth, SLA breaches, throughput, capacity, alerts on what's about to break. Not vanity metrics; the ones that drive today's decisions.
Monthly board packs, weekly all-hands slides, customer-facing performance reports. Generated on schedule, delivered by email or Slack, formatted the way your audience reads.
The layer under the dashboards. We stand up a proper warehouse (BigQuery, Snowflake, Postgres), model your data with dbt or SQLMesh, and version it in git so tomorrow's reports match today's definitions.
The reason your team opens the dashboard: they trust the number. We ship data lineage, freshness alerts, and a definitions doc so 'what does revenue actually mean here' has a single answer.
The hard part of BI is agreeing on what a metric means. We do the definitions work first, then the plumbing, then the visuals. It's why our dashboards get opened.
One working session with your CEO, CFO or head-of-finance, and heads-of-department. Agree on what every key metric means: pipeline, revenue, churn, gross margin, CAC, LTV. Written down, signed off, shared.
Ingest your sources into the warehouse. Model them in dbt or SQLMesh. Build data-quality tests. Nothing lands in a dashboard until the tests pass.
Build the executive + operational dashboards on your tool of choice (Metabase, Preset / Superset, Looker, Hex, Sigma). Iterate in real time with the operators who'll use them.
Automated reports scheduled, Slack alerts wired, training session for your team. Runbooks handed over so your team can extend without us.
New metrics get added as your business changes. Monthly review to trim what's stale and add what's now important. The dashboards stay relevant instead of rotting.
We agree on a specific accuracy standard before we ship (every critical metric matches its source system to the penny; freshness inside the agreed SLA). If any metric fails that standard in month 1, every hour of remediation is on us until it doesn't.
Written into the contract. No small print, no clawback games.
The proof isn’t in the pitch deck. It’s in what shipped and what changed.
“The AI integration into our existing platform automated 80% of our manual workflows. Our team now focuses on strategy instead of repetitive tasks.”
The ones founders and operators ask before we sign. Don’t see yours?
Ask on a discovery callThe tool is 20% of the problem. The other 80% is: which metrics matter, how they're defined, where the data lives, how it flows, and how you keep it fresh. We do the 80% and use whichever tool is right for the last 20%. Buying Looker without the modelling layer is why so many BI projects die.
Yes, for anything above the smallest scale. dbt or SQLMesh for modelling, BigQuery / Snowflake / Postgres for the warehouse, Fivetran / Airbyte / custom for ingestion. For very small businesses we can start on Postgres or Metabase's built-in query layer; upgrade path is clean.
Operational dashboards run near-real-time (2-5 min delay). Executive dashboards run every 15-60 min. Batch reports run on schedule. We tell you upfront what each source can support and design around it.
That is the failure mode we care about most. We measure dashboard opens per week per user; if adoption is dropping, we know before you do and we fix it. Usually it's a definition problem, not a UI problem.
Every critical metric matches its source system to the penny, and every source stays fresh inside its agreed SLA. Miss that in month 1 and we remediate for free until it holds.
First build is a one-time fee sized to the number of sources and metrics. Then a monthly retainer covers modelling maintenance, new metrics, and freshness monitoring. Most engagements pay for themselves inside 90 days on reporting-hours reclaimed.
Book a free consultation. We'll look at what you're tracking today on the call and tell you which dashboard would answer the most questions with the least work.