-90%
Reporting time
97%
Query accuracy
+34
NPS increase
10x
Analyst capacity
Signalify sells analytics to mid-market retail chains. Their customers had rich data but no data scientists to interpret it. Every insight request went through a bottleneck of one overworked analyst.
Natural language to SQL is a solved problem in research but unreliable in production. The system needed to handle ambiguous queries gracefully, explain its reasoning, and never return confidently wrong answers.
We built a RAG pipeline that maps user queries to a curated schema description, generates and validates SQL before execution, and returns results with a plain-English explanation. Guardrails prevent hallucinated column names from reaching the database.
Reporting time dropped 90%. The single analyst now handles 10x the request volume. Customer NPS increased 34 points in the six months after launch.