Data Engineering & Analytics
Pipelines, warehouses, and dashboards that turn scattered product data into decisions — and into fuel for your AI features.
What's included
Data pipelines
Reliable ETL/ELT from your apps, tools, and third-party sources into one warehouse.
Warehouse & modeling
Clean, documented data models your whole team can query with confidence.
Dashboards & reporting
Live metrics for founders, ops, and customers — no more spreadsheet exports.
AI-ready data
Embeddings, feature stores, and clean datasets that make AI features possible.
Stack we use
Good fit if you're
Making decisions from gut feel because data lives in ten tools.
Preparing data foundations before an AI initiative.
Needing customer-facing analytics inside your product.
Use cases we deliver
Data warehouse & pipelines
Consolidate SaaS tools, databases, and files into BigQuery, Snowflake, or Postgres.
Data modelling with dbt
Tested, documented models and a semantic layer.
Dashboards & reporting
Executive, operational, and customer-facing analytics.
Conversational analytics
Ask questions in plain English; get charts and summaries.
AI data pipelines
Incremental embeddings, feature stores, and freshness SLAs for retrieval systems.
Data governance
PII classification, access control, lineage, and quality monitoring.
How the engagement runs
What you receive
- Data audit and architecture
- Ingestion pipelines and warehouse
- dbt models, tests, and documentation
- Semantic layer and dashboards
- Conversational analytics assistant (optional)
- Governance: PII classification, access controls
Frequently asked questions
Which warehouse do you recommend?
Postgres for small scale, BigQuery or Snowflake as volume grows. Discipline in modelling matters more than the vendor.
Can non-technical leaders query the data?
Yes — conversational analytics over a governed semantic layer lets them ask in plain English with explainable answers.
How long does a data foundation take?
A solid foundation for an SMB typically takes 6–8 weeks; enterprise programmes are phased.
Do we need this before AI features?
For reliable AI, yes. Clean, documented, governed data is what makes agents and assistants accurate.
What about data privacy?
PII classification, row-level security, and clear rules on what may leave your boundary are part of every build.
Want your data working for you?
Reply within one business day with a tailored proposal.
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