Running a matrimonial service for a Muslim community in Kerala without a structured database means managing profiles in WhatsApp groups, paper registers, and memory. When a family in Malappuram asks whether there are any profiles from Kozhikode with a girl who has a degree and the family is open to a boy currently studying, you're either pulling from a mental index built over years or you're reading through a folder of printed sheets. Neither scales past forty profiles.
The DFS Mailing template was built to replace that system.
The Match Logic Built Into the Fields
The critical structural decision in this template is the pairing of personal attributes with spouse preference equivalents. Every field that describes the candidate has a corresponding field for what they're seeking in a match.
ജില്ല (District) is the candidate's district — one of Kerala's fourteen districts. ഇണയുടെ ജില്ല (Spouse's preferred district) is a multi-select — the candidate can be open to matches from multiple districts. A girl from Malappuram who is open to Kozhikode or Malappuram matches against boys from either district. That query runs instantly in Memento. Without the structured field, it requires reading each profile manually.
The same pairing structure applies to religious affiliation: മത വിഭാഗം (candidate's sect — Sunni, Salafi, Jamaat, Tablighi, or unaffiliated) alongside ഇണയുടെ മതവിഭാഗം (acceptable sects in a spouse, multi-select). And to physical appearance: നിറം (candidate's complexion, five levels) with ഇണയുടെ നിറം (preferred complexion in a spouse, multi-select).
These preference fields don't impose values — they record what each family has stated. The database doesn't match; the operator filters. But the structured fields make that filtering possible at scale.
Identity and Verification
ആധാർ captures the Aadhaar card number via barcode scan — the fastest identity capture method when processing candidates at a community registration event. മഹല്ല് (Mahal affiliation — the local mosque community organization) is the social verification layer that matters within Kerala Muslim networks. A family can check the mahal name against their own network and independently verify the profile's community standing.
പിതാവിന്റെ പേര് (father's name) is the deduplication field — in a database where common names like Muhammad and Fatima appear dozens of times, the father's name is the distinguishing identifier used throughout Kerala record systems.
The age calculation — datediff(Date Of Birth, Entry Date) / 365 — auto-computes age at registration. The Age/DB radio lets the operator display either the calculated age or a manually entered one, handling cases where date of birth is uncertain.
Education, Employment, and Practical Details
ഭൗതിക വിദ്യാഭ്യാസം (secular education, LP through Degree) and മത വിദ്യാഭ്യാസം (religious education, Fourth Class through Tenth Class Madrasa) are tracked separately. In Kerala Muslim matrimonial contexts, both matter independently. A candidate with a degree but low religious education and another with strong madrasa background and SSLC represent different profiles to different families, and the dual education field captures that without collapsing them into a single metric.
ജോലി (employed: yes/no), ജോലിയെ പറ്റി (job description), and ജോലിക്ക് താല്പര്യമുണ്ടോ (interest in employment, for female candidates) document the economic picture. മഹ്ർ (mahr — the obligatory marital gift in Islamic marriage) captures both the expected amount and the offered amount, which is negotiation-relevant data the matchmaker needs before introducing families.
The ഇണയിലെ സങ്കൽപ്പങ്ങൾ (expectations from spouse) field is free text — the place where everything that doesn't fit a structured field lives. After filtering by district, sect, education, and employment, this is the field that separates compatible profiles from merely matched ones.