AI · E-commerce · Moderation

AI-powered email spam & submission relevance filter.

Using AI to reduce spam submissions by 80% and lower manual review workload — without adding friction for legitimate users.
Client
Withheld (digital-first e-commerce)
Sector
E-commerce / services
Scope
AI form moderation · OpenAI integration
Stack
OpenAI GPT · custom backend
Withheld (digital-first e-commerce)
Withheld (digital-first e-commerce)

80%

Reduction in spam form entries

60–70%

Reduction in manual support workload

100%

Improved registration legitimacy

Real-time

Validation across multiple fields

About the client

Drowning in spam, fake signups, and irrelevant inquiries.

A digital-first e-commerce business operating a service-based website received hundreds of user-submitted entries each week through contact forms and registration pages.

Irrelevant inquiries, spam form fills, and fake customer signups were wasting support-team time and polluting backend databases.

Hundreds of submissions / week

High submission volume, low signal.

Valid · Suspicious · Spam

Intelligent classification, minimal user friction.

The requirement

Filter spam intelligently — without friction for real users.

Manual moderation was inefficient and error-prone. The client needed automated detection and rejection of irrelevant submissions, real-time moderation to flag suspicious accounts, improved data integrity, and seamless integration with existing backend systems.

They chose OST for our ability to implement custom AI workflows using OpenAI's language models, backed by secure, scalable backend engineering.

What we developed

An AI-enhanced form moderation system.

We built and deployed an AI-enhanced form moderation system integrated with OpenAI and custom backend logic, combining semantic filtering, multi-layered registration validation, and an automated scoring workflow.

Submissions are classified as Valid, Suspicious, or Spam, with automated workflows for activation, flagging, or rejection — and a dashboard for manual review of edge cases.

A featured deliverable

AI-powered semantic filtering

A featured deliverable

OpenAI models evaluate each submission for relevance, tone, and language patterns, detecting spam signals like promotional links, gibberish, and irrelevant keywords — then flagging or auto-rejecting invalid entries.

Outcome & benefits

From high-friction manual review to intelligent automation.

By integrating AI into their submission pipeline, the client transformed an error-prone manual process into a scalable, intelligent moderation system.

Key operational metrics we helped track.

Beyond filtering, we surfaced the signals the client needed to continuously improve submission quality and react to evolving spam techniques.

  • 80% reduction in spam form entries
  • 60–70% lower manual review workload
  • Cleaner, verified registration database
  • Improved support efficiency through automation
  • Higher customer trust and engagement
  • Human override retained for edge cases

Tech stack

What's under the hood.

OpenAI inference wrapped in secure backend workflows, tuned for real-time performance and privacy.
OpenAI GPT modelsSemantic relevance scoringOTP email verificationDisposable-domain detectionPhone–IP geomatchingAutomated scoring engineModeration dashboardReal-time validation API
Confidentiality notice Client name and identifying details are withheld under our agreement. The work, scope, methodology, and outcomes shown are accurate. Named references are available to qualified prospects under a mutual non-disclosure agreement.

Spam and fake signups eating your team's time?

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