We are building a local services marketplace platform where operators/service providers register and get automatically generated SEO profile pages using AI.

Our current backend stack:

• Spring Boot

• PostgreSQL

• Queue/worker architecture

• OpenRouter for AI generation

• Fixed UI template with structured AI-generated content

Current Workflow

User clicks "Create Profile" in frontend
↓
Frontend sends operator data to Spring Boot
↓
Spring Boot saves raw operator data in PostgreSQL with status = PENDING
↓
Spring Boot pushes generation job into queue/worker system
↓
Worker reads operator data and calls OpenRouter
↓
OpenRouter returns structured content JSON
↓
Worker validates JSON and stores generated content in PostgreSQL
↓
Status becomes READY or PUBLISHED
↓
Frontend fetches content and renders fixed UI sections
↓
If generation/validation fails:
status = FAILED
and goes to retry/manual review

Main Problem We Are Facing

The biggest issue is scalability and waiting time during operator registration.

Currently:

• AI generation for a single operator takes around 2–3 minutes

• If 100 operators register simultaneously, generation takes extremely long

• Queue becomes very slow

• Users cannot realistically wait on mobile devices for hours until profile creation finishes

This creates a very poor onboarding experience.

Additional Constraints

We also cannot fully rely on AI-generated content directly because we still need:

• validation

• duplicate checking

• bot prevention

• moderation

• quality review

• accuracy verification

• human-in-the-loop workflows

In some cases:

• manual review may take several hours or even more than a day

• operators cannot wait that long before getting a usable profile

Important Business Constraint

We are an early-stage startup.

So:

• we cannot afford expensive large-scale AWS infrastructure

• we cannot keep many always-running servers

• this traffic spike is occasional, not constant

• we need a cost-efficient architecture

Current Thinking

We are considering:

• validation tags

• verified/unverified status

• delayed content enrichment

• moderation pipelines

But the core issue remains:

How do we make profile creation feel instant for users even if AI generation and moderation are delayed?

Main Questions

We would like suggestions on:

1. How should we architect this system for fast onboarding UX?

2. How do marketplaces usually handle delayed AI/content generation?

3. Should profiles become partially visible immediately before AI generation completes?

4. How should human-in-the-loop moderation work without blocking registration?

5. What queue strategies or async architectures are recommended for burst traffic?

6. How do we avoid long waiting periods during simultaneous registrations?

7. How can we reduce infrastructure costs while still scaling reasonably?

8. Is there a better architecture than generating full AI content during registration time?

9. Should SEO content generation happen later asynchronously instead of during onboarding?

10. How do large marketplaces balance:

• speed

• moderation

• AI generation

• trust/safety

• infrastructure cost

• user experience

Our Top Priority

The most important goal for us is:

Fast onboarding experience with minimal waiting time

Even if:

• AI generation

• moderation

• SEO enrichment

• validation

happen later in the background.

We would appreciate suggestions from people who have built:

• AI pipelines

• async generation systems

• marketplace onboarding systems

• human-in-the-loop workflows

• scalable moderation architectures

• programmatic SEO systems