Your AI stack.Built, tuned, and operated by us.
Controlled entirely by you.
We deploy, customize, and operate AI.
On your hardware or ours. Open models you control, or the commercial ones.
One team. Zero handoffs.
Built for the organizations that can't afford to get it wrong
- Utilities
- Banking
- Healthcare
- Government
- Enterprise
Why most AI projects fail
Most AI projects fail in the gaps between vendors. The hardware vendor blames the software, the software blames the network, and the model provider blames your data. Months pass, nothing ships, and no one owns the outcome.
We were built to close that gap and keep it closed. One contract, one team, one standard. From the power plug to the prompt.
We don't sell a model, a box, or a platform. We sell the result.
Your data never leaves
Your data, your models and your hardware all stay inside your jurisdiction. Nothing routes through a third-party cloud unless you choose it.
No vendor agenda
We're independent, with no vendor quota to fill. What we recommend fits your case, not a sales target. We agree how ROI gets measured before anything is bought.
Exit-ready, no lock-in
Documented architecture, open standards, and your own licenses. If we ever part ways, everything keeps running, and it's all yours.
One accountable operator
Everything runs under one contract, with a single team and a single point of contact. When something needs fixing, there is no one to blame but us, so we fix it.
Explore
Every layer, end to end.
From the power plug to the prompt. Below is the map. Each section goes deep.
Infrastructure
Power, cooling, racks, fiber, GPU servers, and the software stack that runs on them. From an empty room to a production cluster.
Deployment
On-premises, hosted dedicated, or via API. All private. What changes is where the hardware lives and who manages it.
Applications
What AI can actually do for you: answers from your documents, agents that act, models tuned to your rules.
Managed Services
Your AI, operated 24/7. Monitoring, updates, security, optimization, support.
Models
Frontier or open-weight? We help you choose, and we run whatever you pick.
Glossary
AI, in plain English. Every term on this site, explained without jargon.
Not sure where to start? Start here.
AI Readiness Assessment. Strategy and roadmap. Team training. The first step for most of our clients.
Who we are
From the field, by people who do the work.
Prime TPS built this practice for organizations that cannot route sensitive workloads through a third-party cloud. Utilities, financial institutions, healthcare, and government, in Puerto Rico, the Caribbean, and across Latin America.
That capability is grounded in field operations running Puerto Rico’s critical infrastructure since 2013. An AI deployment is an infrastructure project before it is a software project. The same crew that has kept Puerto Rico's critical infrastructure online installs the GPU servers.
How we deliver
Four layers, fully accountable.
Most vendors own one layer and subcontract the rest. We are accountable for the whole stack. That's the difference.
Built on critical infrastructure
Headquartered in Puerto Rico, serving the Caribbean and Latin America with a bilingual engineering team in English and Spanish.
US federal jurisdiction for regulated data, cultural and language proximity to LATAM, and one time zone for the Americas.
FAQ
Common questions.
Can we run AI without sending our data to a third-party cloud?
Yes. We deploy open-weight models on-premises, on hardware you own, so your data never leaves your building. An air-gapped option is available for the most regulated workloads.
Do we have to buy GPUs, or can you host the hardware?
Both. We offer three deployment modes: full control on-premises (you own the hardware), hosted dedicated (private GPUs on a monthly cost, no purchase), or frontier models via API. Many clients start with one and evolve.
Should we use open-weight or frontier models?
For most enterprise workloads the gap has nearly closed. Open-weight gives you full control and zero data leakage; frontier gives maximum intelligence via API. Often the best setup is both: open-weight for volume, frontier for the hardest problems.
What does it cost to run AI in production?
Running it in-house means at least two ML engineers plus a security engineer, well over half a million dollars a year before a single GPU. Our Managed Services runs it for a fraction of that, on one predictable monthly invoice.
We're not sure where to start. What's the first step?
An AI Readiness Assessment. We evaluate your data, infrastructure, use cases, compliance, and team, then hand you a written report with a phased roadmap. No commitment beyond the assessment.
Do you work with organizations outside Puerto Rico?
Yes. We are headquartered in Toa Baja, Puerto Rico and serve the Caribbean and Latin America, with a bilingual (English/Spanish) engineering team and US federal jurisdiction for regulated data.
The same discipline, applied to your network.
Prime builds and operates carrier-grade telecom infrastructure island-wide across Puerto Rico. These networks are engineered to stay online through hurricanes. Caribbean and Latin America on request.
Contact
Let's talk about your AI.
Not knowing where to start is the usual starting point. We'll help you figure out what you need.
Talk to an engineer →