GoApercu
Labs
SQL-Native AI Platform on BigQuery
GoApercu Labs embeds AI capabilities directly into BigQuery, enabling analysts and engineers to query unstructured data, run semantic search, and invoke LLMs — all from standard SQL. Designed for data teams who want AI without leaving their existing warehouse workflow.
KEY_METRICS
PLATFORM_OVERVIEW
SQL-Native AI Functions
GoApercu Labs exposes AI capabilities as BigQuery remote functions. Data teams call `AI.CLASSIFY()`, `AI.EMBED()`, `AI.SUMMARIZE()` directly in SQL — no Python, no notebooks, no context switching. The functions are backed by Vertex AI and custom fine-tuned models.
Unstructured Data Insights
Clinical notes, support tickets, and free-text fields are notoriously hard to query. Labs adds a semantic layer that embeds unstructured columns at ingestion time, making them queryable via vector similarity — all within standard BigQuery syntax.
Healthcare Data Scale
Originally built to power a global health data platform serving 2M+ patient records. The SQL-native approach allowed clinical analysts to run AI-powered cohort queries without engineering involvement, reducing time-to-insight from days to minutes.
Zero-Migration Architecture
Labs integrates as a BigQuery connection — no data movement, no schema changes, no new infrastructure. Existing tables and pipelines remain untouched. AI functions are added as a layer on top, making adoption frictionless for existing data teams.
TECH_STACK
DATA LAYER
- >Google BigQuery
- >BigQuery Remote Functions
- >Apache Beam (pipelines)
- >Cloud Storage
AI / ML
- >Vertex AI (Gemini)
- >Custom fine-tuned models
- >Embedding APIs
- >SQL UDFs
FRONTEND
- >React + TypeScript
- >BigQuery REST API
- >Recharts (query viz)
- >Tailwind CSS