Postgres full-text search over counselling reports, ranked by relevance. Filter by school, grade, or report kind.
Yash Bhatt. Top RIASEC dimensions: Realistic (23), Investigative (41), Artistic (25). The pattern suggests strong fit for analytical
Yash Bhatt. Top RIASEC dimensions: Realistic (23), Investigative (41), Artistic (25). The pattern suggests strong fit for analytical
Yash Bhatt. Top RIASEC dimensions: Realistic (23), Investigative (41), Artistic (25). The pattern suggests strong fit for analytical
Yash Bhatt based on assessment battery + 3 counselling sessions. Top pathway: data science (consistent across RIASEC, DAT V, and self
Yash Bhatt (Grade 12). Discussion focused on design as a pathway and the family's view on stream
Yash Bhatt completed the mock CET aptitude battery. Performance: Maths 68/100, Logical Reasoning 86/100, English 59/100. Time management
Yash Bhatt completed the mock CET aptitude battery. Performance: Maths 66/100, Logical Reasoning 69/100, English 92/100. Time management
Yash Bhatt completed the mock CET aptitude battery. Performance: Maths 72/100, Logical Reasoning 59/100, English 94/100. Time management
Yash Bhatt based on assessment battery + 3 counselling sessions. Top pathway: medicine (consistent across RIASEC, DAT V, and self
Yash Bhatt was engaged today. We explored their interest in medicine, discussing pathway options at the intersection of curiosity
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.