Postgres full-text search over counselling reports, ranked by relevance. Filter by school, grade, or report kind.
Ananya Shetty explore the recommended track for one quarter; revisit at term-end. Action: introduce Ananya Shetty to alumni
Ananya Shetty. Top RIASEC dimensions: Realistic (61), Investigative (69), Artistic (93). The pattern suggests strong fit for analytical
Ananya Shetty. Top RIASEC dimensions: Realistic (61), Investigative (69), Artistic (93). The pattern suggests strong fit for analytical
Ananya Shetty. Top RIASEC dimensions: Realistic (61), Investigative (69), Artistic (93). The pattern suggests strong fit for analytical
Ananya Shetty based on assessment battery + 3 counselling sessions. Top pathway: data science (consistent across RIASEC, DAT V, and self
Ananya Shetty completed the mock CET aptitude battery. Performance: Maths 90/100, Logical Reasoning 63/100, English 73/100. Time management
Ananya Shetty completed the mock CET aptitude battery. Performance: Maths 89/100, Logical Reasoning 59/100, English 77/100. Time management
Ananya Shetty completed the mock CET aptitude battery. Performance: Maths 61/100, Logical Reasoning 55/100, English 66/100. Time management
Every reports.text and counsellor_note is indexed by Postgres tsvector (english config). One GIN index, refreshed on insert.
Search box runs plainto_tsquery + ts_rank_cd. Filter chips (school, grade, RIASEC, kind) compose into the same SQL — no client-side filtering.
ts_headline wraps matches in <mark> tags so counsellors see the evidence in context.
Top 30 sorted by rank × recency. The aim is < 200 ms server-side on the full corpus, no Elasticsearch needed.