AI Search & Recommendation Services
Search and recommendation services help organizations connect customers, teams, and products with the right information faster. Pento builds semantic search, ranking, and recommendation systems that improve discovery and engagement.
How AI search and recommendation systems drive revenue
Traditional keyword search often misses intent, while generic recommendation engines struggle to reflect your business rules. Pento designs search and recommendation systems that improve relevance in real operating environments.
We built a recommendation engine for an ecommerce platform with 2M+ SKUs. Add-to-cart rate up 34%. Fully live in 7 weeks.
What you get
- Deployed recommendation API integrated with your product catalog
- A/B testing setup to measure lift against your current baseline
- Reranking logic you can tune as business rules change
Semantic search vs. keyword search: what the upgrade looks like
Pento's approach combines retrieval, ranking, personalization, and feedback loops into one practical system. We tailor each implementation to your data model, catalog structure, user journeys, and performance requirements.
How we build and deploy search and recommendation systems
Discovery and Relevance Assessment
We start by reviewing your catalog, content sources, user behavior, business rules, and current discovery experience.
This helps us identify where users drop off and where recommendations can create measurable value.
Retrieval, Ranking, and Personalization Design
Next, we design the architecture for indexing, semantic search, ranking features, recommendation logic, and experimentation.
This includes how relevance signals, embeddings, and business constraints should work together.
Pilot and Relevance Validation
Before scaling broadly, we validate the experience with pilot implementations and offline or live evaluation.
We measure ranking quality, click-through behavior, conversion impact, latency, and edge cases.
Production Integration and Optimization
After validation, Pento integrates the solution into your product, content platform, or internal tools.
We support APIs, experimentation, analytics, and monitoring so your team can manage relevance over time.
Product recommendation AI: personalization at scale
From ecommerce discovery to internal knowledge retrieval, better search drives engagement and conversion.
Ecommerce product discovery and cross-sell recommendations that increase conversion
Semantic site search for content, documentation, and support that understands intent
Internal knowledge retrieval for teams and operations
Personalized ranking for feeds, listings, and marketplaces
Recommendation engines for catalogs, media, and learning platforms
Demand forecasting integrated with your recommendation layer
Pento combines practical machine learning experience with strong product engineering and data infrastructure expertise. We build systems that improve relevance without losing sight of latency, governance, or commercial outcomes.
Clients choose Pento because we provide:
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Ready to improve discovery and conversion?
If your organization wants to improve relevance, increase engagement, or help users find the right result faster, book a 30-min scoping call and we'll identify the highest-impact change to your discovery stack.