Turn your data into decisions.
Data pipelines, dashboards, and analytics platforms that surface the metrics that drive your business.
Start a projectProblems we solve
You've probably lived at least one of these. Here's exactly how we take it off your plate.
The situation
Your data lives in a dozen tools and no two reports ever agree.
What we do
We consolidate it into one trusted source and model it, so a number means the same thing everywhere.
How we'd run it
- Discover
We map every source, its quality, and the questions you actually need answered.
- Define
One source of truth chosen and the core metrics defined — in writing, agreed.
- Develop
Reliable pipelines that move, clean, and model the data on a schedule.
- Deliver
A warehouse your team can query with confidence, tested against known answers.
The situation
You're sitting on data but have no clean way to query, visualize, or act on it.
What we do
We build the pipelines and dashboards that turn raw tables into the handful of numbers that drive decisions.
How we'd run it
- Discover
We learn which decisions the data is supposed to support.
- Define
The metrics that matter, defined once so they don't drift per report.
- Develop
Modeled data feeding dashboards built for the questions you ask most.
- Deliver
Self-serve dashboards, plus training so your team explores without waiting on us.
The situation
Every board deck and investor update is a manual scramble across spreadsheets.
What we do
We automate the reporting so the numbers are current, consistent, and defensible, without the week-long fire drill.
How we'd run it
- Discover
We pin down exactly which metrics your board and investors track.
- Define
Metric definitions locked so the same number can't be computed two ways.
- Develop
Automated pipelines feed the reporting straight from source data.
- Deliver
Live dashboards and exports, so reporting is a click, not a scramble.
The situation
Dashboards exist, but nobody trusts them, so decisions still get made on gut feel.
What we do
We fix the pipeline reliability and add tests, so the dashboard is something people act on instead of second-guess.
How we'd run it
- Discover
We find where numbers break, lag, or silently go stale.
- Define
Data-quality checks and freshness targets agreed for the critical metrics.
- Develop
Tested, monitored pipelines that fail loudly instead of serving bad data.
- Deliver
Dashboards with a freshness and quality signal, so trust is visible and earned.
Toolkit
The stack behind it
The tools we reach for. We pick per project, not per fashion, and these are what we run in production today.
Languages
- Python
- SQL
- R
- Scala
Warehouses & Lakes
- Snowflake
- BigQuery
- Redshift
- Databricks
- ClickHouse
- DuckDB
Pipelines & ETL
- Airflow
- Prefect
- dbt
- Spark
- Kafka
- Airbyte
Databases
- PostgreSQL
- MySQL
- MongoDB
- Elasticsearch
BI & Visualization
- Tableau
- Power BI
- Looker
- Metabase
- Superset
- Plotly
Cloud & Orchestration
- AWS
- Google Cloud
- Azure
- Docker
- Kubernetes
Who this is for
- Teams who are making decisions on gut feel because their data is siloed or unreliable
- Companies with raw data but no clear way to query, visualize, or act on it
- Teams preparing investor reporting, board decks, or operational dashboards