Data strategy

One language for your data

A semantic layer defines what your numbers mean once, so dashboards, apps and AI all give the same trusted answer. Without the retyping.

Try the demo → See why it matters ↓
app.semantic-layer.demo
Net revenuemeasure · finance
governed
Active customersmeasure · 90-day rule applied
one definition
Regiondimension · joins resolved
ready
Gross marginmeasure · cached
fast
The problem

Everyone asks the same question. Everyone gets a different answer.

🧮

Metric drift

"Revenue", "active customer" and "margin" are redefined in every dashboard, spreadsheet and SQL script.

🗄️

Cryptic schemas

Tables like tbl_inv_itm_x mean something only to the engineer who built them. Business users can't self-serve.

🐢

Analyst bottleneck

Every new question becomes a ticket. Days of waiting for a number that should take seconds.

What it is

A semantic layer sits between your data and everything that uses it

Data sourcesWarehouse, databases, APIs
→
Semantic layerMetrics · dimensions · joins · security · caching
→
BI & dashboards
Apps & APIs
AI & agents

Define the business meaning of your data once. Reuse it everywhere.

Benefits

What your business gains

🎯

Single source of truth

One governed definition per metric. Finance, sales and product finally agree.

⚡

Self-serve speed

Business-friendly names let non-technical users explore data without waiting on engineering.

🔐

Governance & security

Row- and column-level access, audit trails and PII masking enforced centrally.

🚀

Performance & cost

Pre-aggregations and caching cut warehouse queries and compute spend.

🔌

Tool independence

Switch or add BI tools without rebuilding logic. No vendor lock-in.

🤖

AI-ready data

Give LLMs a governed vocabulary so natural-language answers are accurate, not hallucinated.

Impact

Typical outcomes after adoption

1
definition per metric, reused across every tool
Days → seconds
to answer new business questions
↓ spend
on warehouse compute through caching and pre-aggregation
100%
of access rules enforced in one place

Outcomes are illustrative; actual gains depend on starting point and data volumes.

Why now

AI needs a semantic layer more than BI ever did

😬

LLM on raw SQL schema

Guesses joins, invents columns, mixes up "revenue" with "bookings". Answers look confident and are quietly wrong.

✨

LLM on a semantic layer

Chooses from governed metrics and dimensions. Joins, filters and business rules are already encoded, so answers are consistent and auditable.

# "What was net revenue by region last quarter?" measure: net_revenue dimension: region time: last_quarter # → the layer generates correct, secured, cached SQL
Where it fits

For your business and your product

🏢

Internal business

  • Consistent KPIs across finance, ops, sales
  • Governed self-service analytics
  • Faster reporting and audit readiness
  • Natural-language data assistants
📦

Your product

  • Embedded analytics for customers
  • Multi-tenant data isolation built in
  • One API for web, mobile and partners
  • AI features on trustworthy data
How we help

We know how to build one

🧩

Bespoke semantic layer

Designed around your domain: YAML/metadata-driven definitions for tables, metrics, glossary terms and business rules, with a query engine and LLM-ready API tailored to your stack and security model.

Full controlDomain-specific rulesAI-native
🧊

Built on Cube.dev

Open-source, battle-tested headless BI. We model your cubes and measures, configure pre-aggregations, access control and REST / GraphQL / SQL APIs, and connect your BI tools and apps.

Faster to launchOpen sourceRich ecosystem
Our approach

From messy schema to trusted answers

1 · DiscoverAudit sources, KPIs and pain points
→
2 · ModelDefine entities, metrics, glossary, rules
→
3 · BuildBespoke engine or Cube.dev deployment
→
4 · ConnectBI tools, apps, AI agents
→
5 · GovernTest, monitor, evolve

Start small with one domain and a handful of metrics, then expand.

Next step

Let's define your data once

See it working on real data, then book a short discovery session. We'll map your top metrics, recommend bespoke or Cube.dev, and outline a pilot.

Try the demo → Book a discovery call