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AI-Native Software Engineering & Transformation

Asking AI is easy.Knowing what to ask isn’t.

We help you decide what’s worth transforming with software and AI — then we build, rescue and run it, with engineering judgment and more than a decade of taking systems to production.

Since 2015 · 400+ projects · 60+ clients · 10 countries

Companies and organizations that have trusted us for years.

See all cases
Intermundial
Connect
Walmart
Tigo
Seguros G&T
Grupo Entre Ríos
ProSim
Enapsys
Mabe
Banrural
Neonet
Prensa Libre
Combexim
Prenda Crédito Avanza
Ayuda en Acción
Cáritas de Guatemala
JICA
World Food Programme
USAID
DAI
Palladium
ConnectEd
AGEXPORT
The problem

Building got easy. Making it work didn’t.

Today, one person can turn an idea into code in a matter of days.

That doesn’t remove the hard decisions. It moves them.

Architecture, security, data, integration, maintainability and operations still decide whether an application becomes a product — or technical debt.

Your starting point

What are you trying to solve?

You don’t need to know which service to buy. Tell us where you are today, and we’ll show you where to start.

There are plenty of opportunities. Not all of them are worth it.

Opportunity Map · illustrative example

Risk and feasibility set the order within each quadrant.

Part of the job is saying where AI doesn’t belong.

Recommended starting pointTransformation

AI Opportunity Assessment

Before you build, you define.

Cian-OS™ Product Blueprint · 3–4 weeks
  1. InputYour process
  2. DiscoveryProduct definition
  3. ProductUX prototype
  4. ArchitectureTechnical architecture
  5. OutputRoadmap · fixed investment
Grupo Entre Ríos · Guatemala 52% → 85% capacity used per truck See case

In three to four weeks: product definition, prototype, architecture and a fixed investment.

Recommended starting pointTransformation

Product Blueprint

Working isn’t the same as ready.

Readiness profile · illustrative example
ArchitectureReview
SecurityAttention
MaintainabilityReview
DataSolid
OperationsAttention
AI readinessReview

Start free: 12 questions, four minutes. If there’s risk, we confirm it against your code.

Recommended starting pointEngineering

Readiness Check → Software Readiness Assessment

Don’t add more hands. Add engineering capacity.

Engineering Pod · illustrative example
RoadmapQ1Q2NowQ3Q4
Technical leadershipIncluded
EngineeringPer roadmap
AI + Cian-OSIncluded
CapacityPlannedActiveAvailable
SprintBuildVerifyRelease
Intermundial · Spain 8 dedicated engineers See case

A stable team inside your roadmap, delivering every sprint.

Recommended starting pointEngineering

Engineering Pods

Deployment isn’t the end. It’s where accountability starts.

Software Care · illustrative example
ReliabilityStable
SecurityProtected
ObservabilityMonitored
ReleasesScheduled
IncidentsReviewed
Continuous improvementPrioritized
Prenda Crédito Avanza · Guatemala −19% written-off portfolio−8% delinquent portfolio See case

Reliability, security, observability and continuous improvement, with defined response times.

Recommended starting pointEngineering

Software Care

Cian-OS™

10+ years building software. Now at AI speed.

AI lowers the cost of execution. It raises the value of judgment. Each square is a project delivered since 2015 — and what we learned became Cian-OS™, the system that connects the decision to the operation: what should exist, how it gets built, how it’s verified and how it holds up in production.

400+projects delivered since 2015
  1. 01Intent

    Business & Product Intent

    Are we solving the right problem?

    • Business outcome
    • Users
    • Constraints
  2. 02Foundation

    Product & Engineering Foundation

    Are we making the right decisions before we accelerate?

    • Architecture
    • Data
    • Security
  3. 03Build

    Human + AI Engineering

    Are humans and AI agents working with the right context and boundaries?

    • Repository context
    • Bounded tasks
    • Reviewing changes
  4. 04Verify

    Continuous Verification

    Can we prove that what was built satisfies the original intent?

    • Automated testing
    • Security checks
    • Production readiness
  5. 05Operate

    Production & Continuous Improvement

    Can the system stay reliable, understandable and economically sustainable?

    • Observability
    • Incidents
    • Improvement backlog
Explore Cian-OS
Case studies

Outcomes that are still working years later.

The business outcome first. Then the system that made it possible.

Agribusiness · Guatemala

Grupo Entre Ríos

An AI model that plans weekly pickup from production, weather and demand.

One of Guatemala’s three largest rubber exporters. Its operation depends on collecting raw material from dozens of points every week.

  1. 52%capacity used per truck, before
    • Production
    • Weather
    • Demand
  2. AI model
  3. Weekly pickup plan
  4. 85%capacity used per truck, after
Engineering decision: three inputs and one operational output, measured with the metric the business cares about.

Cian-OS · retrospective reading

  1. Intent, no record
  2. Foundation, verified

    01 The operational foundation first: the platform for rubber intake, budgeting and maintenance, plus the corporate website.

  3. Build, verified

    02 With that foundation in production, the AI model integrated into the existing weekly planning.

  4. Verify, verified

    03 The result was evaluated against the 52% utilization baseline.

  5. Operate, verified

    04 The systems keep evolving with the same team.

Read the full case

Insurance · Spain

Intermundial

A dedicated team of senior engineers, integrated into the workflows of a European InsurTech.

8 dedicated engineers

A Spanish InsurTech specializing in travel insurance and assistance, operating across Europe. Scaling development capacity with senior nearshore engineers working in sync with the Spain-based team.

“Ciancoders has the ability to create solutions at an international level and standard, and its service is top quality.”

Adrián Cortés · CIO, Intermundial · client for 8 years
Intermundial website: travel insurance search
Intermundial’s public website, one of the systems the team develops and maintains.

Cian-OS · retrospective reading

  1. Intent, client-owned
  2. Foundation, client-owned
  3. Build, verified

    Since 2018 Claims platform, website and customer app.

  4. Verify, no record
  5. Operate, verified

    Today Continuous development and maintenance.

Read the full case

Financial services · Guatemala

Prenda Crédito Avanza

An AI model that scores the risk of every application, inside the existing approval flow.

01The decision

Every application had to be assessed consistently.

The information already lived in the platform, but it wasn’t used to decide.

02The system

  1. Application
  2. Risk estimate
  3. Credit team decision
Conceptual representation of the flow, not the client’s interface. The model lives inside the existing approval flow; the credit team still makes the call.

03The result

−19% written-off portfolio

−8% delinquent portfolio

Cian-OS · retrospective reading

  1. Intent, no record
  2. Foundation, verified

    2018 The lending platform goes live and starts recording every application and its outcome.

  3. Build, verified

    Late 2022 The risk model is integrated into the approval flow. The credit team still makes the call.

  4. Verify, no record
  5. Operate, verified

    Today More than six years of work together; the platform remains the operation’s core system.

Read the full case
See all case studies
Engineering economics

More engineering capacity for every dollar invested.

In a traditional model, human effort is spread across nearly every execution task. In Cian-OS, it is concentrated where judgment matters most — and AI accelerates the rest.

≥20%

lower investment than our own equivalent traditional delivery model.

If we misjudge the effort for the agreed scope, the overrun is on us.

ActivityTraditional modelCian-OS
Problem definition Human judgment Human judgment
Architecture Human judgment Human judgment
Implementation Human judgment AI executes · an engineer verifies
Testing Human judgment AI executes · an engineer verifies
Documentation Human judgment AI executes · an engineer verifies
Review & acceptance Human judgment Human judgment

Where human effort is concentrated in each model. A qualitative view, not a measurement.

2015founded, in Quetzaltenango
400+projects delivered
60+clients
10countries with clients
About

Built in Latin America. Working globally.

Ciancoders was founded in Guatemala in 2015 with a simple idea: create technology opportunities from Latin America by building software that solves real problems.

Frequently asked questions.

What is Cian-OS?

Cian-OS™ is Ciancoders’ engineering system. It defines how people and AI agents turn business problems into software that is verifiable, maintainable and operable. It is organized into five systems — Intent, Foundation, Build, Verify and Operate — with cross-cutting controls for security, quality, cost and AI governance.

Do I need to know what to build before talking to Ciancoders?

No. If it isn’t clear yet, we start with an AI Opportunity Assessment: we review your processes, data and systems, rank the opportunities by impact, effort, risk and feasibility, and recommend a first step. We also tell you where AI isn’t the answer.

How is AI transformation different from software development?

Transformation decides what should exist: which process to change, on what evidence and in what order. Development — Product Engineering — builds, verifies and ships what was decided. We do both, so the recommendation comes from people who can then build it and run it.

How is pricing set?

We work on a fixed investment against a defined scope. Because AI accelerates execution, pricing comes in at least 20% below our own equivalent traditional delivery model. If we misjudge the effort for the agreed scope, the overrun is on us.

Can you work on an app built with Lovable, Bolt, Replit or Bubble?

Yes. We start with a Software Readiness Assessment to understand how solid the foundation is, then recommend whether to stabilize, rebuild parts of it, or keep building.

Do I own the code?

Yes. Code and documentation live in your repository from day one.

Do you work in English and in US hours?

Yes. We work in English or Spanish, on schedules compatible with the US and Canada.

Will you sign an NDA?

Yes — before we see any of your code or business data.

See all questions

Your problem doesn't need more code.

It needs the right decisions behind the code.

Tell us what you're trying to solve. We'll help you decide whether to transform a process, build something new, rescue what you have, add capacity — or take a different path.

30 minutes · No commitment · English or Spanish