AtlasCloud AI infrastructure is now live inside EdgeUno’s data centers across Latin America. This gives regional teams local access to a full AI inference platform, so they no longer need to send data abroad to build with AI.
The Unfulfilled Promise of AI in Latin America
Artificial Intelligence (AI) is not the future. It is the engine of the present. We have all seen the slide decks filled with charts about how AI will change our businesses.
For many companies in Latin America, the reality looks different. AI adoption runs into an invisible wall. That wall is not a lack of skills or software budget. It is the location of the compute.
For years, running demanding AI work has meant sending data abroad. This includes training Large Language Models (LLMs), running financial models, and computer vision. Companies in the region had no local option.
This costs companies twice over:
Hidden Costs. Cross-border data transfer and offshore compute raise operational costs.
Data Risk. Moving sensitive data across borders raises sovereignty and compliance concerns.
This is not just a technical problem. It shapes real business decisions, like which projects get funded and which stay stuck as a pilot. Teams often delay AI projects simply because the compute they need sits on another continent.
EdgeUno and AtlasCloud Join Forces
At EdgeUno, our mission is simple: build Latin America’s digital foundation. That is why we formed a strategic alliance with AtlasCloud, a full-modal AI inference platform. Together, we break down the wall between Latin American businesses and world-class AI compute.
This partnership combines two strengths. EdgeUno brings its network footprint of 17 countries and more than 50 data centers, which puts infrastructure at the edge of the network. AtlasCloud brings the AI inference layer that turns that infrastructure into a platform developers can use right away.
Neither piece works as well alone. Infrastructure without an inference layer is just servers. An inference platform without local infrastructure still sends your data offshore. Together, they connect users, developers, and compute in the same region.
What AtlasCloud’s One API Gives You
AtlasCloud is an AI inference platform that connects developers to more than 400 AI models through one unified API. This covers large language models, image generation, video models, and audio, all through one API key.
Instead of managing a separate integration for every AI provider, a team connects once. That one connection reaches the full model catalog, so there is no need to manage separate vendor relationships for each modality.
AtlasCloud’s API is OpenAI-compatible, so teams already using the OpenAI SDK can switch with minimal code changes. Developers can sign up, generate an API key, and make their first request within minutes.
The catalog spans five modalities: text and reasoning, image, video, audio, and 3D. Large language models on the platform include DeepSeek, Qwen, and GLM, called by model ID through the same endpoint used for image and video requests.
This range matters because AI moves fast. New models launch often, and each one has a different strength. Some are built for coding help. Others are built for image, video, or voice generation.
Instead of testing and integrating each new model on its own, a team can access new models through the same API key on day one. That saves engineering time and keeps the whole workflow in one place.
Seedance 2.0 and Media AI in One Unified API
The AtlasCloud catalog spans both media AI and language models. This includes video models, image tools such as Flux and GPT Image, and new models added as soon as they launch.
One example is the Seedance 2.0 API, which supports quad-modal inputs of text, image, video, and audio. It gives developers control over camera motion and character actions across shots, all from one prompt.
AtlasCloud also supports native MCP connections, so teams can connect the platform to their existing tools and workflows. This means one setup covers the entire workflow, from a single API call to a finished asset.
AtlasCloud’s model gallery lets developers browse community creations for inspiration before writing their own prompt. A model explorer feature also lets a team run one prompt across several models and compare the results side by side.
These features help teams break the habit of testing models one at a time in separate tabs. Everything sits inside the same account.
The Atlas Cloud Advantage
Across every industry, from a fintech team in São Paulo to a media studio in New York, the same problem shows up. Tech teams end up managing too many vendors just to cover text, image, and video generation.
Atlas Cloud replaces that patchwork with one account. That saves your developers’ skills for building product, not for wiring together yet another API.
Enterprise Grade Security You Can Trust
AI infrastructure only helps a business if it passes a security review. AtlasCloud is SOC 2 certified and HIPAA compliant, with data encrypted at rest and in transit. HIPAA compliance and SOC 2 certification together give the enterprise grade security that matters for any company that handles customer records or financial data.
AtlasCloud backs its platform with a 99.9%+ uptime commitment. For companies with stricter data needs, private deployment options keep sensitive workloads on dedicated servers instead of shared ones.
Running this compute inside EdgeUno’s regional data centers means Latin American companies get this security close to home, and save money they would otherwise spend on offshore transfer fees. Sensitive data no longer needs to leave the country.
Want help scoping a secure AI deployment? Contact EdgeUno’s specialists to review your data residency and compliance needs.
Why Local Compute and the Edge Matter for AI
Edge infrastructure places servers close to where users and data live. For AI, this cuts the distance data has to travel before a model can process it.
Shorter distances mean lower latency for requests. This matters for real-time uses, like a chatbot, a voice tool, or a live video generation feature.
AI cloud platforms built with local nodes also improve availability. If one site has an issue, requests can route to another location nearby instead of failing or crossing an ocean. This also supports disaster recovery, since workloads are not tied to a single facility.
Local infrastructure helps distributed teams too. Developers in different cities can connect to the same regional platform, instead of routing every request through a data center on another continent.
The Business Impact: From Technology to Gain
This alliance is not only a technology upgrade. It changes what AI costs your business and what it can earn back.
| Before the Alliance | With EdgeUno and Atlas Cloud (Local) |
|---|
| High cost from using compute outside the region | Lower operational costs and fewer data transfer fees |
| Legal risk from moving data across borders | Data stays local, which simplifies compliance |
| Slow adoption due to offshore setup complexity | Fast access to GPU clusters, with no long wait |
| AI treated as a pilot project or cost center | AI treated as a source of revenue |
AtlasCloud uses a pay-as-you-go pricing model, with no monthly minimums and no seat fees. Users only pay for what they generate, with rates listed on the platform’s pricing page.
With powerful compute close by, companies cut the time and cost needed to train machine learning models. This shortens the path from idea to return on investment.
The GPU resources behind this setup can scale up or down based on demand. This elastic model means a team gets instant access to more compute during a launch, without paying for idle servers the rest of the year.
Faster access to compute also speeds up how quickly new AI features reach users. A team no longer waits on offshore provisioning cycles to test and deploy a new application.
Need to model what this could save your team? Talk to an EdgeUno specialist about a cost comparison for your current AI workloads.
We Are Already Building the Future
This is not a long-term plan. It is a rollout already underway. The first high-density GPU clusters are live in key regional hubs:
- São Paulo, Brazil
- Bogotá, Colombia
- Santiago, Chile
- Buenos Aires, Argentina
- Mexico City, Mexico
By placing AI compute at the edge, close to where data is made and users connect, EdgeUno and AtlasCloud make AI a practical tool. This applies across financial services, gaming, and healthcare.
Financial services teams can run fraud checks and risk models on local infrastructure, keeping customer data in-country. Gaming and media studios can generate art, video, and voice assets for players without routing every request offshore. Healthcare providers can use HIPAA-compliant infrastructure to build tools that handle patient data responsibly.
Is your city on the list? Reach out to EdgeUno to confirm access and setup timelines for your market.
Expert-Led Support to Launch Your AI Inference Platform
Local infrastructure alone does not guarantee results. Our expert AI engineers bring hands-on support to every deployment, from first API call to full-scale production use.
Atlas Cloud exclusive optimizations are built into the platform, tuning GPU utilization so requests run efficiently at scale. EdgeUno’s team connects that platform to your existing systems and supports your developers through setup.
This support covers more than the first API call. As your usage grows, EdgeUno’s engineers help manage costs, plan capacity, and keep your integration running as new models launch.
For companies moving off manual servers or a patchwork of vendor accounts, this expert led setup removes the guesswork. Your team gets one point of contact instead of several support tickets across different platforms.
The choice between AI power and low cost is over. World-class local infrastructure lets Latin American businesses and governments capture the real value of AI, without sending data or money offshore.
Ready to move your AI strategy into action? Contact EdgeUno’s team to explore how AtlasCloud’s AI-ready infrastructure can support your business in Latin America.
How to Get Started on AtlasCloud’s AI Inference Platform
Getting connected takes a few simple steps. EdgeUno’s team can walk your developers through each one.
- Sign up for an account and generate your API key from the console.
- Pick your first model, whether that’s a language model, an image tool, or the Seedance 2.0 API for video.
- Send your first request using the unified API, with no separate setup per model.
- Scale as needed, using the same key across your entire workflow.
This process usually takes minutes, not weeks. Your team keeps its existing code, since the API follows the OpenAI-compatible format.
AtlasCloud describes its approach as a full-modal AI inference platform, built to remove the extra work of managing separate providers. EdgeUno adds the regional infrastructure that keeps that platform close to your users and your data.
If your team has questions before signing up, EdgeUno’s specialists can walk through the setup with you first. That includes reviewing your current stack and mapping out which models fit your use case.
Common Questions About AtlasCloud AI Infrastructure
Here is the short story on what changes for your team, in plain terms.
How many models can I access with one AtlasCloud API key?
AtlasCloud gives developers access to more than 400 AI models through one account and one API key. This covers text, image, video, audio, and 3D generation.
Is AtlasCloud secure enough for regulated industries?
Yes. AtlasCloud holds SOC 2 and HIPAA certifications, with data encrypted at rest and in transit. Private deployment is also available for teams with stricter compliance needs.
How fast can a developer integrate AtlasCloud?
Setup takes minutes, not weeks. A developer can sign up, generate an API key, and make a first API call the same day, with no waitlist.
Does AtlasCloud charge monthly fees?
No. AtlasCloud runs on a pay-as-you-go model, with no monthly minimums or seat fees. Teams pay only for what they generate.
Where can I use EdgeUno’s AtlasCloud infrastructure in Latin America?
EdgeUno currently runs AtlasCloud compute in São Paulo, Bogotá, Santiago, Buenos Aires, and Mexico City, with more regional hubs planned.
Can AtlasCloud handle image, video, and voice generation together?
Yes. The platform’s media AI features cover image generation, video models, and audio or voice generation, all reachable through the same API and account.
Do I need separate integrations for each AI provider?
No. AtlasCloud’s one unified API replaces the need for separate vendor integrations, so your developers manage one connection instead of many.
