Routes every workload. Logs every decision.
FrIdA sits between every AI application and every compute environment. It decides where workloads run, enforces compliance at execution time, and logs every decision — under your jurisdiction, against your policies, in your audit trail.
The difference is everything. In regulated markets, an AI workload that touched the wrong data or ran in the wrong jurisdiction is not fixable in an audit report. It is a regulatory event. A compliance officer defending a CNBV, BACEN, or CMF inquiry does not need a post-hoc explanation of what happened. They need proof the wrong thing could not have happened in the first place.
Run the workload wherever. Review the logs later. Hope the auditor accepts your explanation.
Policies are constraints, not reports. Non-compliant workloads don't run. Every route that does run is logged, signed, and defensible.
FrIdA reads every workload's metadata — data classification, customer jurisdiction, SLA, cost envelope — and routes it to the compute environment that satisfies every constraint. Public cloud for cost-optimized batch, on-prem for regulated data, air-gapped for sensitive workloads. The application developer never decides. The policy does.
Residency, compliance framework, data class, retention, encryption requirements — all evaluated before the workload dispatches. Policies are authored in code, reviewed like code, versioned like code. Non-compliant workloads halt. Compliant ones proceed with a signed policy evaluation attached.
FrIdA selects the optimal model for each task — open-source for sensitive data, commercial frontier models for low-risk general tasks, domain-specific fine-tunes for regulated workflows. Model choice becomes a policy decision, not a developer decision. When a new model releases, FrIdA can adopt it without touching application code.
Every decision FrIdA makes is recorded: which workload, which policy, which model, which environment, with what metadata, at what timestamp, authorized by whom. The audit log is immutable, queryable, and exportable. When audit asks, you have a defensible answer in seconds. Not a week of forensics.
Customers change deployment strategies without rewriting applications. Migrate from public cloud to sovereign region. Add an on-prem cluster. Extend to a new country with different residency rules. The application code does not change. FrIdA re-plans the route.
Applications emit requests with metadata. FrIdA evaluates policies, selects compute and model, dispatches the workload, and writes an audit record. Every step defensible.
Every FrIdA policy lives in your repository. Pull-requested. Reviewed by compliance. Signed off by risk. Deployed like any other piece of your production system. No shadow configuration. No manual gates. No surprises.
# Policy: LatAm banking residency + compliance # Applies to: Tier-1 bank production workloads apiVersion: frida.saptiva.ai/v1 kind: RoutingPolicy metadata: name: latam-banking-residency version: 2.4.0 owner: [email protected] spec: applies_to: data_class: [pii, financial, kyc] customer_jurisdiction: [MX, BR, CL, CO] requires: residency: in_country provider_type: [on_prem, sovereign_cloud] encryption_at_rest: customer_managed_keys encryption_in_transit: tls_1_3 forbids: providers: [us_hyperscaler_default_regions] models: [external_api_with_training_retention] audit: log_level: full retention: 7y signed_by: compliance_hsm on_violation: action: halt notify: [[email protected], [email protected]]
FrIdA does not ship with a preferred model, cloud, or hardware stack. It routes across all of them. The compatibility matrix exists to make that explicit — not to sell you a particular option.
A Tier-1 Central American bank replaced stalled hyperscaler pilots with FrIdA. The governance constraints that blocked them for eighteen months were not a bug in the previous platform. They were the difference between AI that can run and AI that can't.
The workloads hyperscalers can't run. The compliance framework your systems integrator couldn't navigate. The pilot that stalled in procurement. A Forward Deployed Engineer will respond within 48 hours.
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