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Built by AshaVidMarketplace / ImmigrationBuilt 2026

Verixa

A two-sided platform where the hard problem was not matching supply to demand, but making credibility legible before any money changes hands.

ClientConsultantAdminBooking core
Three role-based workspaces over one booking core with enforced slot integrity.
  1. Interface

    What the user touches

    • Next.js
  2. Application

    Where the rules run

    • TypeScript
    • Prisma
    • NextAuth
    • Resend
  3. Intelligence

    Models and ingestion

    • OpenAI
  4. Data

    What persists

    • Neon PostgreSQL
  5. Platform

    What it runs on

    • Vercel Cron

A compact view of the venture

Venture
Verixa
Category
Two-sided marketplace
Stage
Live platform
Core challenge
Making consultant credibility verifiable
Our role
Product design and full-stack build
Focus areas
Booking engine, role-based portals, lifecycle automation

Why we started building this

Immigration advice is a market with unusually asymmetric information. The applicant rarely has the context to judge whether the person advising them is licensed, competent, or appropriate for their case — and the cost of getting it wrong is measured in years.

That asymmetry is what makes the category attract both excellent practitioners and bad actors, and it is why a generic booking tool does not solve the problem. The scheduling is trivial. The trust is not.

Verixa was built around licensing as the entry condition, with the rest of the platform — portals, scheduling, content — arranged to make that verified status visible and useful.

In a market where bad advice is expensive and irreversible, the product problem is verification long before it is booking.

What we built

A full-stack Next.js marketplace with self-contained modules for booking, dual-sided portals, SEO content aggregation, and system administration, running on Neon PostgreSQL via Prisma.

  • Five-step booking engine

    Real-time scheduling with strict slot conflict prevention, so two clients can never hold the same consultant slot.

  • Role-based workspaces

    Separate, granular views for clients, consultants, and system administrators.

  • Automated lifecycle pipelines

    Cron-driven email campaigns through Resend, paired with native in-database notifications.

  • Self-managing backups

    Scheduled database serialisation, gzip compression, and secure delivery to the administrator — no external backup service in the loop.

  • AI content engine

    Headless scrapers using OpenAI structured outputs to produce continuous discovery content for search.

  • Native edge analytics

    A first-party page-view tracker that attributes traffic to specific consultant and article IDs without a third-party script.

Why this needed to exist

  • A marketplace with no verification layer becomes a lead-generation site for whoever markets hardest.

  • Double-booking is not a minor bug in a consultation marketplace — it destroys the credibility the platform exists to provide.

  • Two-sided products carry two distinct sets of expectations, and collapsing them into one dashboard fails both.

  • Marketplaces are demand-constrained early, so discovery traffic had to be part of the product rather than a later marketing project.

  • Operating costs matter pre-revenue, which ruled out a stack of paid third-party services for backups and analytics.

How we framed the opportunity

Most decisions in the build trace back to the same principle: the platform earns its position by being the place where verification is cheap for the client to check.

Licensing is the entry condition, not a profile field

Verified status is what the product sells. Everything else is infrastructure supporting that claim.

Conflict prevention belongs in the data layer

Slot integrity is enforced where it cannot be bypassed, rather than trusted to client-side validation.

Build the boring infrastructure in-house

Backups and analytics were written natively rather than outsourced, keeping the running cost of an early marketplace near zero.

Discovery content is a product surface

The AI content engine exists because a marketplace without inbound demand is a directory nobody visits.

Where the existing options fell short

What already existed

  • Directory listings of consultants with contact details.
  • Generic scheduling tools that any practitioner can adopt individually.
  • Firm websites that ask the client to take credibility on faith.

What was missing

  • Licensing verification as a structural condition of being listed.
  • A booking flow that guarantees slot integrity across both sides.
  • A consultant workspace rather than just a public profile.
  • Discovery content that brings applicants in at the research stage.

The decisions that shaped the product

Verification before visibility

Licensed status gates presence on the platform, which is the entire reason a client should prefer it to an open search.

Design each side of the market separately

Clients, consultants, and admins each get a workspace shaped around what they actually do, not a shared dashboard with hidden fields.

Keep the platform cheap to run

Native backups, native analytics, and serverless scheduling keep fixed costs low while the marketplace finds demand.

How it came together

  1. Phase 1

    Schema, auth, and roles

    Model consultants, clients, availability, and bookings in Prisma, with NextAuth role separation from the start.

  2. Phase 2

    Booking engine and portals

    Build the five-step scheduling flow with conflict prevention, then the client, consultant, and admin workspaces on top.

  3. Phase 3

    Lifecycle automation and discovery

    Add cron-driven email pipelines, native notifications, self-managing backups, edge analytics, and the AI content engine.

Where the product stands today

  • A live two-sided marketplace with three distinct role-based workspaces
  • A five-step booking engine with enforced slot conflict prevention
  • Cron-driven lifecycle email campaigns via Resend plus in-app notifications
  • Automated compressed database backups delivered without a third-party service
  • An AI-driven SEO content engine using OpenAI structured outputs
  • First-party edge analytics attributing traffic to consultant and article IDs

What building this taught us

  • In high-stakes categories, verification is the product.
  • Booking integrity has to be enforced where it cannot be bypassed.
  • Two-sided means two products, and pretending otherwise fails both sides.
  • Demand generation belongs in the build, not in a later marketing phase.
  • Writing your own boring infrastructure is often cheaper than subscribing to it.

We build the products we would want to operate ourselves.

Verixa is one of the ventures we design, build, and run in-house at AshaVid.