The AI infrastructure layer for regulated enterprises in Latin America. Applications that ship in two weeks. An orchestration engine that enforces compliance at execution time. Deployment modes — cloud, hybrid, on-premise, air-gapped — governed by the same policy framework.
Each page below goes deep on one layer.
Production AI applications for regulated workflows.
Credit origination. KYC. Regulatory reporting. Customer operations. Production-grade applications deployed by an embedded FDE in two weeks. The apps clear compliance because the platform underneath them does.
Routes every workload. Logs every decision.
Sits between every AI application and every compute environment. Routes by residency, latency, cost, and policy. Enforces compliance at execution time. Every decision logged. Every policy auditable. Swap the model, change the cloud, change the regulation — the platform stays the same.
Cloud. Hybrid. On-premise. Air-gapped.
Public cloud. Private sovereign cloud for jurisdictional control. On-premise for your own compute. Air-gapped for workloads that cannot touch the internet. One platform. One policy engine. Deployment mode as a configuration, not a replatforming project.
What clears a risk committee is the posture, not the pitch.
Data residency enforced by architecture. Audit trails on every routing decision. Role-based access, institution to user. Subprocessor transparency. Responsible disclosure, continuously monitored. The baseline that makes everything else deployable.
Every FDE engagement ships with a structured capacitation program. Run inside your organization. Your team gets autonomous on what we deployed.
Every module maps to a specific capability you deployed. Your team learns to operate, extend, and audit the applications without us. Autonomy is the exit criterion.
New module each cycle. Capacitation closes in weeks — not the months enterprise software procurement takes. Each module opens the next use case.
If the only reason you still need Saptiva AI is that your team can't operate the platform, we haven't delivered. Capacitation is how dependency becomes capability.
ACMES's team audits their own policy files. Ibero's faculty extends their own Studio apps. The exit criterion isn't training completed — it's capability owned.
Every architectural decision traces back to one of these. Our customers cannot afford for them to be otherwise.
Enforced at execution time by FrIdA's policy engine, not by contract. A workload that violates your residency rule doesn't route — the platform refuses to execute. Residency is architectural, not administrative.
You choose the model, the cloud, the deployment mode. The platform follows. Swap the LLM — FrIdA routes around it. Change the cloud — the same policy applies. If we can only keep you by trapping you, we haven't earned the relationship.
Every routing decision, every policy evaluation, every workload execution produces an immutable record — readable, exportable, regulator-ready. If something goes wrong, you can prove what the platform did and why. Baseline for regulated production.
Production from day one. An embedded FDE lands inside your team, ships the first use case in two weeks, stays until it runs. We're not optimizing for demos. We're optimizing for what still runs eighteen months later.
If you're evaluating AI infrastructure for a regulated institution and want to go below the overview — architecture, security posture, residency, deployment mode — an FDE responds within 48 hours. Not a sales sequence.