The promise, proven

Measurable results, in weeks

We’re not asking you to trust a promise. These are real projects, implemented and running in Chilean companies: each one validated with a pilot in about a month, at a fraction of the cost of a traditional consultancy.

Traditional consulting would make you wait almost a year for something like this. We do the opposite: we validate and implement a real pilot in about a month, with measurable results from the start and at a fraction of the cost. Every case below is the proof.

Agribusiness

Field layout optimization and picker tracking

Challenge

Fields with an inefficient layout that forced workers to cover excessive distances. There was also no visibility into the real productivity of pickers in the field.

Solution

Mathematical layout optimization

An algorithm that computes the optimal field layout to minimize the distances workers travel.

Picker tracking system

Digital logging of each worker’s productivity in real time.

Result

Reduced travel distances across the fields, full real-time visibility of productivity per picker, and improved season planning.

OptimizationLayoutProductivity
Transportation

Cost minimization and transport reconciliation

Challenge

Unoptimized transport costs and a manual process for reconciling what was planned, what was executed, and what was weighed on the scale.

Solution

Cost optimization

A cost-minimization model that factors in the optimal use of carriers.

Mobile app connected to the ERP

An application for carriers integrated directly with the management system.

Weighbridge integration

A direct connection to the scale for automatic weight reconciliation.

Automatic reconciliation

Automatic cross-checking of what was planned, executed, and weighed.

Result

Lower transport costs through optimal carrier assignment, elimination of reconciliation discrepancies, and full traceability of the process from planning to the weighbridge.

OptimizationMobile appERP integrationIoT
Retail / Pricing

Dynamic pricing agent for price strategy

Challenge

A manual price-setting process that failed to respond to changes in demand, competition, or seasonality. Margins were eroded by the commercial team’s late reactions.

Solution

Competitive analysis agent

Automatic monitoring of competitor prices and detection of adjustment opportunities.

Demand elasticity model

Prediction of the impact on volume from price changes by category and channel.

Result

A significant impact on annual revenue thanks to data-driven price adjustments, with real-time response to market changes.

Machine LearningPricingCompetitionAutomation
Lithium Mining

Mass balance to determine the % of lithium processed

Challenge

A lithium processing plant needed to precisely calculate the percentage of lithium recovered at each stage. The mass balance was done manually in Excel once a month, with incomplete data and high uncertainty.

Solution

Real-time data capture

Integration with flow, concentration, and weight sensors at every point of the processing circuit.

Automated mass balance

An algorithm that reconciles input, output, and recirculation data to calculate the % of lithium recovered per stage.

Continuous monitoring dashboard

Real-time visualization of the balance with alerts when recovery falls below the optimal threshold.

Result

Daily visibility of the % of lithium recovered (previously monthly), early detection of efficiency losses, and improved total recovery thanks to timely process adjustments.

Machine LearningIoTOptimizationLithium Mining
Mining

Dining hall scheduling at a mining site

Challenge

A dining hall for 1,200 workers with capacity for 300 at a time. It collapsed between 12:00 and 12:30 with lines of up to 40 minutes, while after 1:00 p.m. it sat empty. Lost productive time and food waste.

Solution

Lunch shift scheduling

An algorithm that assigns time windows per crew, considering location on site, shift, and operational constraints.

Mobile notification

Each worker receives their lunch time on their device, with the flexibility to swap with coworkers.

Real-time monitoring

Headcount in the dining hall using computer vision to dynamically adjust the flow.

Result

Elimination of waiting lines (from 40 minutes to under 5), even distribution of flow across 2 hours of service, reduced food waste, and improved staff satisfaction.

OptimizationComputer VisionSchedulingMining

Do you have a similar challenge?

Let’s validate your case with a real pilot in about a month, at a fraction of the traditional cost.

Let’s validate your case in 1 month