Recommendation Systems
Hire Recommendation Systems Specialists In Latin America
At Inti, our Optimization & Recommendation services deliver
tailored decision-support tools—combining advanced
optimization algorithms with intelligent recommendation
engines—to help you allocate resources efficiently and
personalize user experiences at scale.
Why Optimization & Recommendation Matters
- Maximize Efficiency: Solve complex allocation, routing, and scheduling problems to reduce cost and waste.
- Drive Engagement: Surface the most relevant products, content, or offers for each user to boost satisfaction and conversion.
- Scalable Personalization: Move beyond one-size-fits-all rules with engines that adapt to changing behaviors and inventory.
Our Two-Pronged Approach
- Optimization Modeling: Craft mathematical formulations—linear, integer, or constraint-based—to capture your operational goals and business constraints.
- Recommendation Engine Development: Build scoring and ranking systems—using collaborative, content-based, or hybrid techniques—to suggest the right items to the right users at the right time.
Our Workflow
Problem Definition & Data Assessment
- Collaborate with stakeholders to translate business objectives into formal optimization goals (e.g., cost minimization, throughput maximization) or recommendation targets (e.g., click-through rate, basket size).
- Audit your data sources—sales logs, inventory feeds, user behavior—to understand what inputs drive each model.
Optimization Modeling
- Linear & Integer Programming: Formulate resource allocation, production planning, and logistics problems with clear objective functions and constraints.
- Constraint Programming & Heuristics: Address complex combinatorial challenges—fleet routing, workforce scheduling—using rule-based solvers, genetic algorithms, or simulated annealing.
- Scenario Analysis: Run “what-if” experiments to compare trade-offs and stress-test your plans.
Recommendation Engine Development
- Collaborative Filtering: Leverage user–item interaction matrices to uncover patterns of co-behavior (e.g., “customers like you also bought…”).
- Content-Based Filtering: Match item attributes (categories, tags, descriptions) to user profiles or past interactions.
- Hybrid Approaches: Combine signals—behavioral, contextual, and inventory—to balance discovery and relevance, reducing cold-start issues.
Deployment, Monitoring & Refinement
- Integration: Expose solvers and recommendation APIs via microservices or embed them within your existing platforms.
- Real-Time & Batch Processing: Support both live decision requests (e.g., online recommendations) and periodic planning runs (e.g., weekly production schedules).
- Performance Tracking: Monitor key metrics—objective value gap, recommendation click-through, adoption rates—and iterate on model parameters and constraint definitions.
Sample Tools and Technologies
Optimization Solvers
CPLEX
Gurobi
Google OR
Modeling Languages:
AMPL
Pyomo
JUMP
Recommendation Frameworks
Surprise
Implicit
LightFM
Engineering Stack
Python
PosgreSQL
Docker
Visualization & Dashboards
Power BI
Tableu
Ploty Dash
BenefitsYou’ll See
- 10–30% cost savings through optimized routing, staffing, and inventory allocation
- 20–40% uplift in engagement and conversion from personalized recommendations
- Agile decision-making enabled by scenario-driven optimization and A/B-tested recommendation rules
- Transparent trade-offs documented in interactive dashboards for stakeholder buy-in
Case Study Highlight
Dynamic Delivery Routing & Upsell Recommendations
A regional logistics provider teamed with Inti to:
Optimize daily route plans for 150
vehicles, reducing total miles by
18%
Recommend add-on services
(e.g., expedited handling,
packaging upgrades) based on
customer profiles and delivery
patterns.
Result: Delivery costs dropped by
$250K annually, and upsell
attachment rates rose by 22%.
Frequently Asked Questions
We parameterize your constraints so you can update rules—fleet size, delivery windows, labor availability—via a user-friendly interface without rewriting models.
We fall back on content-based and rule-based recommendations, then seamlessly incorporate collaborative signals as your data grows.
Yes. We design microservices for low-latency recommendations and scheduled jobs for heavy planning tasks, ensuring both speed and depth.
Begin your journey with Inti today
Talk to an expert for free!
About
Inti Consulting Services LLC is a company based out of Miami, FL. We aim to provide US companies with advanced talent from Latin America to take advantage of the amazing talent that exists in the region.