Product-data infrastructure for AI commerce

Make your catalogue AI-ready.

Oblivion helps growing merchants diagnose, structure and enrich catalogue data so products are easier for AI shopping and discovery platforms to understand, surface and hand off to purchase.

Serving merchants since July 2025
Commerce intelligence layer
SourceProduct catalogues
SourceInventory + policies
OblivionStructure. Enrich. Verify.
OutcomeAI-readable products
OutcomeStronger discovery
OutcomePurchase-ready handoff
Operating track record
Serving merchantsSince 2025
Hands-on AI-commerce readiness support
Government pre-seed grant & funding received
DTU Incubation Center2025
Early-stage institutional support
Government pre-seed grant & funding received
IIT Madras Incubation Centre2026
Pre-seed growth and innovation support

Practical services for AI-commerce readiness.

Start with the part of the problem that matters most. Each engagement is scoped around your catalogue, operating systems and priority channels—with expert review built in.

01 / ASSESS

AI-commerce readiness audit

Review catalogue quality, product context, inventory signals and the path from AI-led discovery to your storefront.

Prioritised action plan
02 / IMPROVE

Catalogue structuring & enrichment

Clean and organise attributes, variants, descriptions and merchant context so products can be interpreted with greater confidence.

Human-verified output
03 / ENABLE

Platform & transaction readiness

Define the data flows, integrations and merchant-owned handoffs needed to support emerging AI shopping journeys.

Implementation roadmap
AI-commerce readiness audit

Turn uncertainty into a prioritised action plan.

A focused review of the product-data and workflow issues that may keep your catalogue invisible, misunderstood or difficult to transact.

Request an auditNo complex setup to begin.
01

Catalogue health review

Assess attributes, variants, taxonomy and the consistency needed to compare products.

02

Product-context gap map

Identify missing descriptions, use cases, compatibility details, policies and buyer answers.

03

Priority enrichment plan

Focus effort on the data improvements most likely to strengthen product understanding.

04

Channel-readiness roadmap

Define practical next steps from AI-led discovery to a reliable merchant-owned transaction.

Expert-led today.
Built to scale.

We stay close to merchant operations while the category is evolving. Human review protects quality now; repeatable workflows become the foundation for software automation over time.

Delivery model · Human-assisted

Merchant context stays in the loop.

Direct collaboration reveals operational constraints and catalogue edge cases that generic tooling can miss.

  • Merchant-specific diagnosis
  • Structured data transformation
  • Quality review and integration support
Product direction · Software-enabled

Automate what proves reliable.

Repeatable delivery patterns inform a scalable product layer for continuous product-data readiness.

  • Reusable catalogue workflows
  • Automated checks and enrichment
  • Multi-platform orchestration

Built for product-led merchants.

For growing businesses with meaningful catalogue depth, fragmented commerce data and ambition to enter new discovery channels—without a dedicated AI-commerce infrastructure team.

CATALOGUE

Complex product ranges

Variants, attributes and use cases that lose meaning in flat feeds.

OPERATIONS

Fragmented systems

Product, inventory and policy data spread across tools and teams.

GROWTH

New discovery channels

A practical way to prepare for AI shopping without rebuilding everything.

See what AI sees in your catalogue.

Start with a focused review of where your product data stands—and what to improve first.

Request an audit