Your data is in a dozen places. An AI can only be as good as the worst one.
Point of sale, ERP, CRM, your product’s own database, documents and the seventeen spreadsheets — pulled into one governed place that people and agents can both quote from.
Pillar 02One version of the truth
Privacy in the plumbing
Who agreed to what, where each number came from, and what has been erased — tracked in the pipeline itself.
What we lead with
- Pipelines that run themselves — pulled on schedule, duplicates removed, missing days flagged
- One warehouse on BigQuery, Databricks or Snowflake
- The meaning layer — “revenue” means one thing everywhere
- Consent and lineage built into the pipe, not written into a policy
Typical stack
DatabricksSnowflakeBigQuerydbtAirflowKafkaMetabaseLookerPower BI
6.5wksMedian time to the first dashboard opened daily
1Governed definition behind every number
24hMaximum data staleness by default
Questions
What clients ask us first.
No. We stand one up as part of the work, sized to your real volumes rather than a vendor tier.
One governed definition per metric, so finance, operations and your AI agents all quote the same number. It is the difference between a dashboard and an argument.
Expected. Most of our retail and manufacturing work involves at least one system that has never had one.
The other five
Six pillars, one contract.
01
Agents in Production
AI that does real work — with a leash you control and a record of every move.
03
Sovereign Compute
Indian GPUs, Indian data residency — 30–50% below the big global clouds.
04
Defensible Systems
Security engineered in, not bolted on — provable to an attacker and an auditor.
05
Compliance as Code
DPDP, ISO 27001, SOC 2 and HIPAA implemented inside your systems.
06
Production Engineering
We make the demo work at 3am, under load, with real money on it.
Next step
Talk to us about data spine.
Tell us what you are running today and what has to be true in ninety days.