LET'S MAKE YOUR IDEAS HAPPEN
WeorchestratedatascienceandAI,operationsresearch,andmodernsoftwareengineeringtoturnyourmostcomplexchallengesintooptimalsolutionsandmeasurableresults.
Itallstartswiththerightquestion
Havingadatacultureisnolongerenough:thevalueisn'tincollectingdata,it'sinthedecisionsitenables.Themostimportantdecisionsdeservequantitativerigor,notjustintuition.
We listen first, we don't propose.
This is how we approach every project:
Understand
We sit down with whoever makes the decision today. Their judgment and daily friction are our starting point.
We adopt what already works.
We build what the problem demands.
We look for the best available decision for challenging problems
Three disciplines. One team.
We design the infrastructure that carries a decision to where it gets executed. With speed.
Not every problem needs all three.
That's exactly why it matters to have them all.
We've already built alongside:
- Turismo Tacna
- EOMMT
- Diphasac
- TeApruebo
What we solve
The industry changes. The nature of the decision, almost never.
Determining which resource goes to which demand, and how much to hold in reserve, when capacity can't cover everything. With live data the model works resource by resource and decides on the full distribution, not on an average.
Examples- Fleets
- classrooms
- crews
- stock
- budget
Building the system where the operation actually happens, from the customer-facing platform to integration with what you already have. For when the bottleneck isn't the decision but the tool used to execute it.
Examples- Web
- e-commerce
- internal apps
- integrations
Ordering in time events that compete for the same installed capacity. Systems that log every event let us model the operation at the level of the individual task, and reschedule when reality shifts.
Examples- Shifts
- timetables
- production
- maintenance
Understanding what's happening before deciding what to change. Organizing scattered data, building the indicators that are missing, and making them visible so the team decides better with what it already has.
Examples- KPIs
- reporting
- diagnostics
- data quality
Defining where to locate the operation and how to connect it, from a daily route to opening a new center. Movement logs replace average times with real trips.
Examples- Routes
- distribution centers
- coverage
- installed capacity
Anticipating the system's behavior so the decision governs the operation. Computer vision turns into data what today only an operator can see.
Examples- Demand
- failures
- performance
- image & video
Deciding today knowing you'll have to decide again tomorrow. Reinforcement learning and recommendation models where every decision changes the scenario for the next one.
Examples- Pricing
- campaigns
- recommendation
- dynamic replenishment
Building the infrastructure that captures, connects, and feeds data back into the operation. Generative assistants put the model within reach of whoever decides, in natural language.
Examples- Integration
- IoT & sensors
- cloud
- monitoring
- assistants
Your challenge might not fit at first glance. Complexity takes many forms, but the structure behind it is the same: what gets decided, who decides, what gets measured, and what's uncertain. Finding those four things is where the work begins.
Driven by rigor, sustained by purpose.
What unites us is a taste for hard problems and a way of working where asking costs little and failing early is worth a lot. You work directly with the people building the solution, and that closeness is something we intend to keep.
“The best part of my job is the client's face when they realize that what they'd been solving by gut feeling for years can actually be modeled.”
Karen Videla — Business Intelligence
Let's make your ideas happen
You don't need to have the problem perfectly defined to reach out. Most of the time, figuring out what the actual problem is is part of the work.
or email us at contacto@iologit.com