Original projectIndia-firstPrivacy-firstGraph product

VanshVriksh — Family Graph

A private, living family graph designed for large Indian families. VanshVriksh makes relationships understandable from every person's point of view while protecting profile ownership, private notes, marriage-linked family boundaries, and the trust needed to grow a shared history across generations.

Origin
Original project
Role
Product, design & technology
Focus
Application
Engineering Area
Web
Domain
Consumer & community
Status
Ideation
01

Why this should exist

Large families deserve a living map, not a forgotten chart

Family knowledge disappears across generations because names, relationships, memories, and responsibilities live in different minds. VanshVriksh gives Indian families a private graph they can grow together while preserving ownership and consent.

02

Problem and product

The problems

  1. 01

    Static family trees cannot explain relationships from each person's point of view.

  2. 02

    Duplicate profiles and marriage links can expose private family information.

  3. 03

    Family coordinators need fast contribution flows that work across languages and lower bandwidth.

What the product delivers

  • Tree-first hierarchy with contextual parent, spouse, sibling, child, and relative creation
  • Viewer-relative relationship groups with explainable graph traversal
  • Phone OTP profile verification, ownership, and visible trust states
  • Human-reviewed duplicate detection and reversible profile merges
  • Marriage-linked family graphs with independent privacy boundaries
  • Profiles with biographies, metadata, portfolio links, social profiles, and field-level visibility
03

Technology used

A stack chosen for the product

Neo4j owns the relationship graph while PostgreSQL owns identity, permissions, private notes, and workflows. Next.js delivers a phone-first PWA, and event-driven services isolate reminders, invitations, and duplicate review from interactive graph changes.

ReactTypeScriptNext.jsNeo4jCypherGraph Data ModelingPostgreSQLDrizzle ORMCloudflarePWAOTP WorkflowsEvent-driven ArchitecturePrivacy by Designi18n
04

Architecture

How the system holds together

  1. 01

    Canonical family graph

    One person node and typed relationship edges support explainable, viewer-relative family traversal.

  2. 02

    Relational trust store

    Accounts, claims, field visibility, encrypted contacts, private notes, and audit stay outside the public graph model.

  3. 03

    Consent-based workflows

    Invitations, merges, marriage links, reminders, and family messages require explicit permissions and reversible operations.

05

Estimated goals

The private digital home for multi-generational families

The tree creates the trusted foundation. Communication, family moments, and carefully reviewed commerce can follow only after privacy and identity work well.

  1. 01

    Ship a private tree MVP for Indian family coordinators.

  2. 02

    Add relationship groups and reversible duplicate resolution after graph trust is proven.

  3. 03

    Test family moments and group gifting with explicit recipient consent.

Future goals are directional estimates and depend on user validation.
06

Extras

Product perspective

Primary audience
Large, distributed Indian families
Business model
Family subscriptions with optional partner services
Product edge
Graph intelligence stays separate from identity and private family data

Non-negotiables

  • A phone OTP proves contact control, not automatic identity, profile ownership, or access to a private family tree.
  • The product never silently merges people or grants access to another family because of marriage.
  • Private notes belong only to their author and are excluded from claims, merges, newsletters, and exports.

Full project notes

Product and engineering deep dive

The project overview adds a concise presentation layer. The complete product details remain below.

From intent to implementation

A product direction shaped around a real use case.

An India-first, privacy-first living family graph that helps large families see their hierarchy, understand relationships, add relatives in seconds, and stay connected across generations. The tree is the main interface: people can create and claim profiles, link families through marriage, select groups such as father’s-side cousins, keep private notes, remember family moments, and safely review possible duplicate profiles.

01 · The product response

What people can do with it

  • Tree-first hierarchy with contextual parent, spouse, sibling, child, and relative creation
  • Viewer-relative relationship groups with explainable graph traversal
  • Phone OTP profile verification, ownership, and visible trust states
  • Human-reviewed duplicate detection and reversible profile merges
  • Marriage-linked family graphs with independent privacy boundaries
  • Profiles with biographies, metadata, portfolio links, social profiles, and field-level visibility
  • Author-only private notes that never transfer through profile claims or merges
  • Birthday, anniversary, festival, call, message, and invitation actions
  • Color-coded family labels, newsletters, and selective group gift planning
  • India-first phone flows, multilingual architecture, low-bandwidth design, and accessible graph views

System architecture

One canonical family graph. Many private points of view.

Neo4j is authoritative for the family graph: every human is one Person node and every family connection is a typed edge. A separate relational security store owns accounts, claims, permissions, encrypted contacts, private notes, audit, and workflows.

Canonical graph

Neo4j stores canonical Person nodes and parent, partner, guardian, adoption, and historical marriage edges. Individual tree layouts remain user-specific views rather than copied family data.

Identity and profile claims

An account is not automatically a person. OTP verification proves control of a contact point; an invitation and explicit profile claim establish ownership or stewardship.

Relationship query engine

Bounded, permission-aware Cypher traversal answers how two people are related, resolves dynamic groups such as all cousins on the viewer’s father’s side, and returns an explanation path.

Separate spouse nodes

A couple is never one database record. Each spouse is an independent Person node joined by one SPOUSE_OF edge; the interface positions the two nodes together.

Safe merge workflow

Names, contact hashes, dates, locations, and relationship overlap create duplicate candidates. Authorized people review evidence before a transactional, audited, and reversible merge.

Event-driven family moments

Queues isolate invitations, OTP delivery, reminders, newsletters, duplicate evaluation, and future gift fulfillment from interactive graph writes.

Privacy boundaries

Graph access, profile-field visibility, contact details, private notes, blocks, and relationship disputes are evaluated on the server. Marriage can connect traversal without silently sharing two families’ private data.

Skills required

Product architecture for a deeply human graph.

Graph and domain modeling

Designing Neo4j Person nodes, typed relationship edges, Cypher traversal, viewer-relative kinship, automatic layout, saved perspectives, and explainable paths at family scale.

Identity, privacy, and abuse prevention

Separating accounts from people, securing phone OTP, protecting minors and memorial profiles, enforcing field visibility, and preventing contact discovery or invitation abuse.

India-first product design

Phone-first and WhatsApp-friendly flows, regional family terms, Unicode and locale readiness, low-bandwidth Android performance, festivals, and large multi-generational family structures.

Distributed workflow design

Idempotent writes, event queues, provider reconciliation, notification preferences, audit trails, and safe failure handling for reminders, invitations, newsletters, and gifts.

Delivery approach

Earn the right to expand beyond the tree.

  1. 01

    Validate the tree-first add experience with Indian family coordinators and finalize relationship, stewardship, language, and privacy rules.

  2. 02

    Ship a private tree MVP with fast relative creation, profiles, invitations, saved roots, private notes, and birthday or anniversary reminders.

  3. 03

    Add marriage-linked graphs, relationship groups, branch labels, duplicate review, and reversible merges after graph trust is proven.

  4. 04

    Layer in WhatsApp-friendly communication, family moments, and consent-safe newsletter drafting.

  5. 05

    Introduce reviewed group gift planning and one fulfillment partner only after recipient selection and privacy workflows are reliable.

Product guardrails

Family trust is more important than graph completeness.

  • A phone OTP proves contact control, not automatic identity, profile ownership, or access to a private family tree.
  • The product never silently merges people or grants access to another family because of marriage.
  • Private notes belong only to their author and are excluded from claims, merges, newsletters, and exports.
  • Dynamic relationship groups must explain why each person was included and allow manual exclusion before messaging, gifting, or exporting.
  • Sensitive classifications such as caste, religion, health, and finances are not default profile fields.
  • The graph must have a keyboard-accessible list alternative and remain usable on mid-range Android devices and Indian 4G networks.

Project sponsorship

Fund this project—from prototype to production.

Help move VanshVriksh — Family Graph from a promising prototype to a reliable production release.

  • Design validation and user research
  • Production infrastructure and security
  • Testing, accessibility, and launch readiness
Choose a sponsorship amount
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