Deterministic Decision Infrastructure,

Systems that decide auditably & controllably.
And respond in milliseconds.

FrekiLabs builds infrastructure for security, routing, and similarity search — no model drift, no black box, no vendor lock-in. When decisions have consequences.

Deterministic not probabilistic

Audit trail for every decision

Fail-closed Security Boundaries

A deterministic control layer spanning routing, execution, detection, and enforcement.

Focus: enterprises that need explainability — without sacrificing performance.
When “the model says so” is not enough.

Why Standard Fails

Three Failure Modes Every Enterprise Eventually Pays For

Performance, security, and compliance collide once ML black boxes and vendor dependencies sit in the critical path.

Unprovable Decisions

Systems that cannot explain why an event was critical lose at the audit — or during the incident.

Yet another “score” without a path

Compliance: “show me the reasoning”

Postmortems without causal chains

Response in the Wrong Time Unit

When detection is “batch”, response is “too late”. Security needs seconds, not days — and no pipeline with five external dependencies.

Detection after damage, not before

SIEM-only = always-late pattern

Costs explode at high event rates

Vendor Lock-in as Risk Transfer

“Managed” often means: no control over costs, roadmap, debugging, or outages. In critical infrastructure, that is not a feature.

Proprietary telemetry & formats

Opaque cost models

External behavior in the hot path

How We Build

Determinism Is Not a “Mindset”. It Is Architecture.

We replace black boxes with formalized mechanics: clear invariants, fixed boundaries, reproducible paths. What is not auditable does not enter the critical path.

From Kernel to API: One Stack, One Ownership.

We design GPU-first, not “CPU + a bit of CUDA”. Core logic stays deterministic. Performance comes from GPU-native design — not from magic.

Output

Reproducible — same inputs, same results.

Explainability

Audit path — score + reasons + chain.

Stability

No drift — no training, no surprise regressions.

Security

Fail-closed — boundaries are formalized.

GPU-native data structures for constant access times

Deterministic similarity & routing (no “probabilities”, no “temperature”)

Proofs & audit trails as first-class output

Vendor-independent control plane (no lock-ins)

Formalized security boundaries (fail-closed, invariants, bounded behavior)

// deterministic decision with audit trail decision = resolve( event, policy: "fail_closed", audit: true ); // proof: why / by what / which chain print(decision.score); print(decision.reasons); print(decision.path); // deterministic => reproducible => auditable

Portfolio

5 Hierarchies — One Principle

Every component is deterministic, auditable, and built for enterprise reviews. No training, no drift, no surprises.

Security & Monitoring

Real-time detection, deterministic alerting thresholds, auditable decision paths.

GPU Storage & Processing

Storage architectures and data processing directly on the GPU. Constant access times, predictable behavior.

Search & Reasoning

Retrieval and decision-making without black boxes. Explainable, reproducible, auditable.

Infrastructure & Core

Control layers, routing, entropy. The foundation for everything else.

Specialized Pipelines

Domain-specific solutions with GPU acceleration. From genomics to game audio.

“Why not just use an ML model?”

Because during an incident, nobody wants to debate whether the score is “really” correct. Determinism delivers reproducibility, evidence, and clear failure modes — that is enterprise-grade.

“What do you get after a call?”

A technical target architecture: data path, integration points, boundaries, audit outputs, and a roadmap with deliverables that are internally reviewable (engineering + security + compliance).

“Integration into existing toolchains?”

Standard outputs: JSON events, webhooks, Syslog/CEF, SIEM export. No isolated solution — clear interfaces and defined semantics.

“Which projects are not a fit?”

If you primarily need “AI vibes”, slides, and demo ML — wrong address. If you want a deterministic engine in the critical path: right place.

Bring Us a Problem with Constraints.

Inputs, event rate, compliance requirements, latency budget. Quick feedback on whether and how the problem is solvable.

Taking away pain points. Expensive ones.

Request Architecture Review

Systems that decide auditably & controllably. And respond in milliseconds.