Search & Discovery | Graas | The System of Intelligence for Retail Commerce
Search & Discovery

Turn customer intent into products to order

Customers come with specific needs, not product names or SKUs. Graas understands intent, evaluates the catalog and commercial rules, understands the user's buying preferences, and recommends products buyers can confidently buy.

How Graas reasons through every product decision.

Customer Intent

Catalog & Customer Intelligence

Commercial Rules & Policies

Best Product Recommendation

Watch the reasoning, not just the result.

A real query, traced end-to-end, from raw intent to a recommendation the buyer can trust.

👤
CUSTOMER QUERY "Looking for an AC for a 12 × 14 west-facing bedroom in Chennai."
STEP 1

Understanding the context

Region & climate signals extracted
Chennai West-facing Humid climate Hot afternoons
STEP 2

Sizing the room

Thermal load computed from dimensions
Room size
12 × 14 ft → 168 sq ft
Required load
1.5 ton
West-facing bias
+12% heat load
STEP 3

Product Graph

Catalog reasoned against the computed load
AC specs matched to load → 4 qualify
STEP 4

Search & Ranking

Ranked by verified buyer reviews from similar climatic conditions, not by generic popularity.

Shortlisted with a clear "why this fits your room."

Not just a list, an explanation, so users buy with conviction.

✦ BEST MATCH

1.5 Ton Inverter AC

Sized for 168 sq ft. Rated for humid climates. West-facing heat load accounted for.

  • Matched to room size & climate
  • Reviewed by buyers in Chennai
  • In stock · eligible for delivery
ALTERNATIVE

Higher Performance

Exceeds spec. Higher efficiency.

For buyers optimising for long-run energy cost.
VALUE

Cost-Efficient Option

Meets all requirements.

Everything the room needs, nothing it doesn't.

Why enterprise buying needs more than search.

Without Graas

KEYWORD SEARCH
Search engines match strings, not needs.
Match keywords: strings, not the need behind them.
Compare specifications: the buyer does the reasoning.
Ignore eligibility & availability: surfaced too late, at checkout.
Returns a product list: long, unranked for the buyer's context.

With Graas

✦ REASONED DISCOVERY
The Knowledge Graph reasons on the buyer's behalf.
Understand intent: the use case, constraints, and context.
Reason over catalog and user preferences: connected in one graph.
Apply business rules and stock availability: before anything is shown.
Recommend the best fit with reasoning: so buyers act with conviction.

Business Outcomes

2x

Higher Conversion

Intent matched to the product that actually fits, not keywords.

+15–25%

Basket Value

Smart upsells and cross-sells from buying history and product relationships in the Knowledge Graph.

Wrong Product Selection

Fewer mismatched purchases & returns.

Consistent Buying Experience

The same recommendations across every channel.