Careem (Uber) · Super App · OpenAI · 2025

Global
AI
Search

Integrated OpenAI to rebuild Careem's broken global search from the ground up, restoring customer trust, achieving 94% intent classification accuracy across 10+ markets and multiple languages, and driving a 67% improvement in search-to-action conversion.

Role

Head of Product Design, Pay & Platform

Timeline

2025

Markets

10+ across MENA

AI Partner

OpenAI

+67%
Search-to-action conversion
94%
Intent classification accuracy
-54%
Time-to-transaction from search
Unified Search, One Query, Every Vertical
INDEXING6 Verticals, 50M+ Items
INTENT MODELGPT-4o
🔍 "birthday party for my daughter" OpenAI
Query Parsing
Tokenization, spell-check, synonyms, language detection
Intent Classification
Multi-vertical scoring, confidence per category
Parallel Retrieval
Real-time index scans, signal weighting
Confidence Ranking
Score aggregation, UI prominence logic
Intent Routing, Confidence Scores
🍰
98%
Food
Birthday cakes, party platters
3 results
🛒
87%
Groceries
Baking supplies, juice, snacks
5 results
🎈
92%
Shops
Decorations, party supplies
4 results
🧹
34%
Cleaning
Post-party cleanup
2 results
🚗
8%
Rides
Guest pickup (low relevance)
,
💳
5%
Pay
Not matched to intent
,
Confidence Thresholds
95%+ Confidence: Prominent position, featured results
75-94% Confidence: Secondary results, "Did you mean?" context
<75% Confidence: Fallback to keyword search + manual browse
Edge Cases Handled
• Empty results for any vertical
• Ambiguous multi-intent queries (carousel pattern)
• Non-English/regional market queries
• Typos, slang, dialect variations
94%
Intent Accuracy
6
Verticals Indexed
50M+
Searchable Items
4
Languages
10+
Markets
+31%
Search Engagement

Audit.
Integrate.
Rebuild
trust.

I led the most comprehensive search redesign in Careem's history, from cross-market research through OpenAI integration to a progressive trust model that visibly improved with use.

01

Cross-market search audit, Directed research with 200+ participants across UAE, Saudi Arabia, Jordan, and Pakistan, documenting every failure mode, frustration point, and workaround customers had developed.

02

OpenAI integration architecture, Worked with engineering leadership to evaluate, select, and design how OpenAI would interact with Careem's service catalogue, customer context, and transaction history.

03

Cognitive load reduction, Redesigned the results architecture to prioritise clarity: AI's best interpretation of intent first, confidence-ranked actions (not listings), and transparent fallback paths.

04

Progressive trust model, Designed a system where search accuracy visibly improved over time per customer. The AI learned from successful completions, with subtle UI signals communicating personalisation without being intrusive.

05

Multi-language intent classification, Ensured 94% accuracy across Arabic, English, Urdu, and Turkish, with cultural nuance handling for regional service expectations.

"AI in product design isn't a feature, it's infrastructure. Rebuilding search on intelligence didn't just fix a feature; it restored trust in the entire super app."

Trust
restored.
Search
transformed.

The OpenAI-powered search restored customer trust in Careem's primary navigation tool and established a new AI platform capability that every vertical could leverage.

Conversion

67% improvement in search-to-action conversion, customers found what they needed and acted on it.

Speed

54% reduction in time-to-transaction from search initiation across all verticals.

Trust Recovery

38% increase in repeat search usage, customers trusted search again.

Cross-service

29% increase in cross-service discovery, customers finding services they hadn't previously used.

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