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data and applied AI services for companies in Chile and Latin America

your business problem, solved with data and applied AI in just the right dose.

Nobody here earns a commission on your cloud or your tools. Your challenge decides the solution.

If you run a business function like finance, operations or sales, or an IT, Data + AI or BI team, Datalized is where you clear whatever is holding you back. Whether it runs in your cloud or ours, your data and your code belong to you from day one, with privacy by design.

Since 2018, more than 80 companies have made their data work for them. With us.

  • Walmart Chile
  • Agrosuper
  • Agroberries
  • iConstruye
  • Red Bull
  • British American Tobacco
  • Ripley
  • Lo Valledor
  • Lemontech
  • Aramark
  • BASF
  • Wild Brands
  • Biotec

your data

when the problem lives in the information. Pick your stage.

your data · 4 services

define


when you don't know where to start.

  • Data assessment: know exactly where you stand.

    In a few weeks, an honest picture of your data and your team: infrastructure, sources, reporting, governance, skills and culture. Then the gaps, a roadmap and a business case you can defend in front of the board.

    talk to us about this →
  • Data architecture: buy only what you'll actually use.

    Cloud, data warehouse, tooling: what to buy and what to build for what's coming, with no reseller agenda behind the advice.

    talk to us about this →
  • Data platform optimization: stop overpaying for the cloud.

    Find where money and time are leaking across your cloud, pipelines and queries, and what to change.

    talk to us about this →
  • Migration discovery: migrate without a leap of faith.

    Before you switch BI tools, clouds or data warehouses: how to do it, what you can reuse and what it will really cost.

    talk to us about this →

your data · 7 services

evolve


when your data can't keep up with what you need.

  • First data warehouse: stop stitching spreadsheets together by hand.

    Everything in one reliable place that grows with you, instead of spreadsheets someone reconciles every month.

    talk to us about this →
  • Data warehouse evolution: grow without starting from scratch.

    New sources, business units or group companies plug into the model you already have.

    talk to us about this →
  • Data integration: systems that finally talk to each other.

    Starting with your ERP: SAP data that's usable and up to date. And outside sources, from market data to customs or suppliers, flow in as if they were your own.

    talk to us about this →
  • Master data: no more bounced orders or duplicate payments.

    Every customer and every product exists once, across the whole company and every system.

    talk to us about this →
  • A trusted foundation for AI: AI that answers from real data.

    For the assistant, agent or Copilot you've already tried or are about to roll out: a shared language for your data, one definition per metric, permissions and traceability. So you can stand behind every answer, and every team shows up with the same number.

    talk to us about this →
  • Your data in plain language: ask your data questions in your own words.

    Answers you can trust, straight from your data warehouse, with one definition per metric and a log of who asked what.

    talk to us about this →
  • Information delivery: get the data to whoever makes the call.

    A dashboard, an alert, an email or an API: whatever channel each decision needs. Reports people actually open and use, not ones that gather dust.

    talk to us about this →

is your data holding you back?

let's talk about your case →let's talk →

your data · 3 services

solve


when there's real money riding on a specific problem.

  • Predictive models: see it coming instead of reacting.

    With the model running inside your operation: demand, customer churn, suggested orders, campaign prioritization, who to collect from first and through which channel, or a critical process variable before it drifts out of range.

    talk to us about this →
  • AI automation: grow without hiring more people for the same work.

    The work someone checks by hand today, handled with AI and good judgment: reimbursements, benefit matching, product classification.

    talk to us about this →
  • Data product: turn your data into a product.

    The thing you could offer with your data, or the tool your team needs and nobody sells, built for you: an API so your customers can query their own information, a market intelligence platform, a continuous audit tool that runs the rules for you.

    talk to us about this →

is there money riding on a specific problem?

let's talk about your case →let's talk →

works across every stage

your team


when the problem is capacity, know-how or time. It's not another rung on the ladder: it works alongside any of the three stages.

accelerate

when you know what to do but you're short on hands.

Senior embedded teams: up to speed from week one.

A team working inside your operation, without adding headcount or spending months hiring. Your delivery arm.

talk to us about adding capacity →

master

when you want your team to run it on its own.

Training on real data: so your team can carry on without us.

Your team learns on its own data and projects, in the tools it already uses: Power BI, dbt or Glue, for example.

talk to us about training your team →

how it's built

work you can stand behind.


  1. AI speeds up the work. A person owns every decision.

    The team works with AI, but no decision is handed over to it. Every judgment call, every delivery and every result has a person behind it who answers for it. And in your solution, AI only comes in when the problem calls for it.

  2. The time AI saves goes back into your project.

    With AI, the team integrates, models, reports and operates faster, always with specs, tests and documentation. That time isn't pocketed: it goes into designing a better solution, getting every delivery right and truly understanding your business.

  3. Commitments you can hold us to.

    What success means is agreed with you before anything gets built. Nothing reaches you without being tested end to end on your real data. You always know what's being done, why, and what comes next. And if something unexpected comes up, all of Datalized is behind you to get it unstuck.

  4. Privacy by design.

    Protecting your data shapes the architecture from day one; it isn't bolted on at the end. Each role sees only what it should, sensitive data is protected at the source, and there's a record of who accessed what. Your team and your AI work on secure data, and you can prove it. Built to comply with Chile's Law 21.719.

ways to work together


Fixed-scope project

when it fits
the problem is well defined and you want results on a fixed date, at a fixed price.
timeline
by milestones, over a few weeks.
what you walk away with
the solution tested on your real data, code and documentation that are yours, and a named owner.
start with a fixed-scope project →

Embedded team

when it fits
you need senior capacity from week one, without adding headcount.
timeline
monthly and ongoing, scaling with your roadmap.
what you walk away with
a team inside your operation, and a clean handover whenever you want to go it alone.
start with an embedded team →

Tell us what hurts. Skip the technical spec.

First you talk the challenge through with us, then you get a proposal.

let's talk about your case →
let's talk →