Data analytics for decisions, not dashboards.
We connect and clean your data, then build pipelines and dashboards in Power BI, Tableau or Looker that people actually use. Tested, monitored and documented, so the numbers stay right — for finance, sales and operations teams that are tired of arguing over whose spreadsheet is correct.
Who it’s for, and what to expect.
For finance, sales and operations teams that are tired of arguing over whose spreadsheet is right, and for leaders who want one trusted number for each metric. We are based in Gurugram and build data pipelines and dashboards for companies across India and abroad.
Most projects start by consolidating and cleaning your sources. A short discovery of your sources and reports, usually a week or two, ends in a fixed estimate for the first set of dashboards. We then build in Power BI, Tableau or Looker on Databricks, Snowflake, BigQuery or PostgreSQL, with a demo on your real data at the end of every two-week sprint. Pipelines are tested, monitored and documented, so the numbers stay right after we hand over. For agents and chatbots on top of your data, see AI development.
What's included
Pick the parts you need, and add more once the first one is working.
Data Engineering
Pipelines that don’t silently rot. Schema evolution, lineage, contracts.
Analytics Engineering
dbt-style transforms with tests. Marts that business users trust.
Business Intelligence
Looker · Hex · Tableau · Power BI. Or our own no-code surface.
ML Platform
Feature stores, training pipelines, model serving — end-to-end MLOps.
Real-time Analytics
Materialised views, streaming SQL, ClickHouse-grade query speeds.
Data Governance
Catalogues, classification, masking, access controls — without slowing teams.
How we work
Discover
A short paid discovery: goals, constraints, a written plan and estimate.
Design
Architecture, UX and a clickable prototype you can react to.
Build
Two-week sprints, with a demo at the end of each one.
Run
Launch, monitor and hand over — or we keep running it 24×7.
Engineering standards
What you can hold us to on every engagement.
Tech stack
Databricks, Snowflake, BigQuery, PostgreSQL · dbt, Airflow · Kafka, Spark, Flink · Power BI, Tableau, Looker, Hex, Metabase
- Sources firstSources consolidated and cleaned before any dashboard is built.
- Pipelines that are testedTransforms with tests, schema evolution, lineage and data contracts, so pipelines do not silently break.
- One number, one definitionA semantic layer with governed metrics, so finance and sales read the same figure.
- A demo on your dataEvery two-week sprint ends with a demo on your real data.
- Governed accessCatalogues, classification, masking and access controls, documented before hand-over.
Questions about data and BI
Power BI, Tableau, Looker and Metabase, on top of Databricks, Snowflake, BigQuery or PostgreSQL.
Yes. Most projects start by consolidating and cleaning sources before any dashboard is built.
It depends on the number of sources, how messy they are and how many dashboards you need. We start with a short discovery of your sources and reports, then give a fixed estimate for the first set of dashboards.
Discovery of your sources and reports takes a week or two. The first dashboards follow in the next few sprints, and every two-week sprint ends with a demo on your real data.
Yes — forecasting, classification and LLM-based search over your own documents. For agents and chatbots, see AI Development.
Let's talk about data and BI.
Software, people or growth — a person replies within one working day.