★★★★
The Central Hotel
Downtown Austin
City views · Restaurant · Fitness center8.7 Excellent$240per night
AI Search and RecommendationsUnlock your search.
Unlock your search.
Build better journeys.
Grow together.
Build search and recommendations your customers love. Connect intent, content and behavioral signals to relevant discoveries, helpful conversations and measurable product outcomes.
+6% MRRNotion search
Learning to Rank implementation
Learning to Rank implementation
PRODUCT WALKTHROUGHFictional travel storefront · Autoplay demo
wayfarer.example / stays / austin•••
wayfarer↗
StaysExperiencesSaved trips
My accountWhere to?Austin, Texas
Check-in — Check-outAdd dates
Travelers2 adults · 1 room
Find your Austin.
Explore stays for your next getaway
4 star hotels in Austin
4 starsFree cancellationPool
★★★★
Garden House Suites
Near Zilker Park
Family suites · Outdoor pool · Near parks9.4 Excellent$265per night
★★★★
The Parkside Residence
South Austin
Spacious rooms · Kitchenette · Garden9.1 Excellent$285per night
01 / 05A query gives you a list.
0:00 / 0:36
Illustrative product experience with fictional properties, prices and availability. Explore the journey from customer intent to a confident choice.
Search that finds. Recommendations that discover.
Understand the intent
Combine exact matching, semantic retrieval and domain signals to find the right answer, even when users do not know the right words.
Make discovery personal
Recommend useful products and content from catalog context and behavioral signals. Balance relevance with freshness, diversity and what each user needs next.
Measure the product outcome
Evaluate ranking quality alongside engagement, conversion, latency and cost. Use controlled experiments to decide what earns a broader rollout.
The people behind the work
Diogo Gonçalves
AI Search and RecommendationsGreat discovery connects what your users need with what your product knows. Diogo brings search and recommendation expertise to the whole journey: retrieval, ranking, personalization and the product decisions that turn relevance into impact.
Led search and recommendations product work at Farfetch before joining TensorOps, and led the Ask Seeking Alpha team.
Production experienceBuilding great search together.
Building great search together.
Real teams. Measurable progress.
NotionKnowledge search+6% MRR
Help users find the right answer earlier.
We implemented Learning to Rank to improve Notion’s search, achieving a 6% improvement in Mean Reciprocal Rank.
Candidate resultsLearning to RankBetter ordering
Mean Reciprocal Rank measures how early the first relevant result appears. Higher is better. Product experiments connect relevance improvements to conversion outcomes.
Financial researchResearch at the scale
of millions of users.
of millions of users.
For a financial research application serving millions of users, we implemented advanced indexing, time series adjustments and hybrid search.
Ticker symbolsLexical precision
+ArticlesEmbedding retrieval
Advanced indexing + time series adjustments
Explore the case study From relevance to revenueUnlock the potential
Unlock the potential
of every search.
Help every traveler discover a stay they love. Relevant recommendations create a smoother journey from curiosity to a confident booking.
Let’s connect relevance improvements to the outcomes your team cares about: more discovery, more engagement and more completed bookings.
RelevanceEngagementConversion
THE BUSINESS CASEIllustrative scenario
Same traffic.
More bookings.
100,000 search sessions per month
4,0003,0002,0001,0000
Current search3.00% conversionImproved search3.30% conversion
+300 bookingsevery month
0%Relative lift20%
Illustrative growth scenario. Traffic stays fixed; the slider changes the assumed conversion lift. Relevance gains such as MRR must be validated separately against bookings in an online experiment.
Building the possibilitiesBring your data to life.
Bring your data to life.
Build the next experience together.
Your catalog, your content and your customer knowledge can do more together. We connect search infrastructure, models and ranking algorithms to unlock that potential.
BUILT TOGETHER. CONNECTED BY RELEVANCE.THE RELEVANCE ARCHITECTUREYour data. Our expertise.
Your data. Our expertise.
More possibilities.
Connect the tools you trust to the experiences your customers love.
Data → understanding → actionExample stack · tailored to your infrastructure
Your data. A better decision.
Agentic search turns a goal into a sequence of retrieval and tool calls. It asks the right follow-up questions, checks structured data and explains the recommendation. Strong relevance is still the foundation.
Built around your prioritiesOne search experience.
One search experience.
Three reasons to get it right.
VP R&D
Make relevance measurable.
Build a representative evaluation set, uncover opportunities and compare retrieval and ranking changes before rollout.
Product leadership
Make discovery convert.
Test whether users reach useful results faster, reformulate fewer queries and complete more of the journeys that matter.
CTO
Make it work in your stack.
Integrate with your index, data and permissions. Set latency and cost budgets, then roll out with monitoring and fallbacks.
Under the hood
Build on the stack you have. Improve the results it delivers.
A complete relevance toolkit
Use the right retrieval and ranking approach for each query, with evaluation throughout.
Learning to Rank & reranking
Combine relevance judgments, content features and behavioral signals to put useful results first.
Hybrid retrieval & advanced indexing
Use lexical matching for exact identifiers and embeddings for meaning. Tune indexing and fusion to your domain.
Recommendation systems
Combine content, catalog context and behavioral signals to personalize discovery. Evaluate useful suggestions alongside diversity, freshness and business outcomes.
Temporal relevance
Account for timestamps, reporting periods and time series context when freshness changes the answer.
Agentic search & structured tools
Turn intent into clarifying questions, retrieval and calls to SQL, catalog or availability services, with source-grounded answers.
Domain-specific embeddings
Tune embeddings to your vocabulary, your content and the way your customers express their needs.
Evaluation & controlled rollout
Track relevance alongside conversion, latency and cost. Validate changes with online experiments and regression checks.
From diagnosis to production
Let’s unlock your next search opportunity.
Diagnose
Discover the potential
Review real queries, search journeys and your current retrieval stack. Agree on what a better result means for your product.
- Representative query set and relevance judgments
- Opportunity mapping across important user segments
- Baseline quality, latency and cost
Evaluate
Prove the improvement
Test retrieval and ranking changes against your baseline, then connect the strongest candidates to a product experiment.
- Hybrid retrieval and ranking experiments
- Offline evaluation and regression checks
- Online test plan tied to a business outcome
Production
Ship and keep learning
Integrate into your product with your team. Monitor relevance and business outcomes as queries, content and user behavior evolve.
- Integration with existing permissions and services
- Staged rollout, fallbacks and observability
- Knowledge transfer and ongoing evaluation
Beyond catalogs and content
The same foundation. Another domain.
Let’s build your next search success.
Bring your ideas and ambitions. Together, we’ll unlock the potential in your data, create better customer journeys and grow your product’s impact.