Data Infrastructure · sub-niche
Semantic layers (2026 reboot).
BI semantic layers, redesigned for LLM-driven exploration.
One-quarter buildSteady — one deal per month
Why now
Every BI vendor is racing to ship AI. Most fail because they lack a semantic layer. The standalone product is real.
What the signal looks like
Repos with dbt / Cube.dev compatibility, LLM-query interfaces, and BI-tool integrations.
Public examples
We name publicprojects + categories only — never founders we track inside the paid product. The buyer’s edge stays inside the product.
- Cube.dev shape
- MetricFlow / Transform shape
- Open-source semantic layer libraries
What this displaces
A Looker LookML file that one person understands.
Our build-vs-invest call
Hard but durable. Fund only with prior BI or data-modeling background. The moat is the semantic-graph + the BI integrations.
Common questions about this niche
- Buyer?
- Data + analytics leaders at mid-market companies.
- Pricing?
- $1-5k/mo per organization.
- Defensibility?
- Semantic graph + LLM-query accuracy + ecosystem.
More inside Data Infrastructure
- Vector database engines — Vector search engines optimized for specific workloads — high-dimensional, hybrid, or local.
- Real-time feature stores — Feature stores with sub-second freshness for online ML.
- Postgres extension marketplaces — Postgres is now the AI database. The extension ecosystem is the next platform.
- Columnar warehouse alternatives — Snowflake / BigQuery alternatives optimized for a specific shape — cheap, fast, or open.