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MLOps & AI Inference Consulting

Production AI,
Faster & Cheaper.

Battle-tested, end-to-end MLOps services and extreme inference optimization. We specialize in making production AI models fast, cheap, and reliable at any scale.

EMEAUAEIndia
10xFaster Model Inference (Target)
60%Cost Reduction (Target)
100%Reproducible Deployments (Goal)
What We Do

End-to-end AI engineering services

From prototype to production-grade systems, we cover the full spectrum.

Extreme Inference Optimization

Achieve drastic speed and cost optimization for AI models using quantization, TensorRT/ONNX, and intelligent serving strategies.

QuantizationTensorRTONNXTriton

End-to-End MLOps Pipelines

Building automated feature stores, CI/CD for ML, retraining loops, canary deployments, and full observability for production models.

CI/CDKServeKubeflowMLflow

Data Drift & Silent Failure Protection

Implementing live statistical monitoring, prediction logging, and automated validation and redeployment pipelines.

Drift DetectionMonitoringAlertsOpenTelemetry

Reproducibility Debt Elimination

Containerizing ML systems with immutable containers and exact dependency pinning to eliminate deployment risks and inconsistencies.

DockerKubernetesDependency PinningIaC
Why Krylox

Built by engineers, for engineers

We don't just advise. We embed with your team, write the code, and own the outcome. Every engagement is hands-on and results-driven.

Deep Technical Expertise

Our team has shipped production ML systems at scale. We know the difference between benchmark performance and real-world reliability.

Fast Time-to-Value

No endless discovery phases. We audit your stack, build a plan, and start delivering in the first week.

Built to Scale

Every solution is designed for growth, from single-model deployments to multi-tenant serving infrastructure.

Global Coverage

Serving clients across EMEA, UAE, and India with enterprise SLAs and timezone-appropriate support.

krylox audit

$ krylox audit --stack production

Analyzing inference pipeline...

Checking drift monitors...

Scanning container configs...

⚠ Latency p99: 480ms (target: 50ms)

⚠ No drift monitoring detected

⚠ Reproducibility score: 3/10

Generating optimization plan...

✓ TensorRT: estimated 8x latency reduction

✓ INT8 quantization: 4x memory saving

✓ Drift alerts: ready to configure

$ krylox optimize --apply

Deploying optimized serving stack...

✓ Done. Latency p99: 52ms

8x

latency reduction

60%

cost saved

How We Work

From audit to production in weeks

A no-nonsense engagement model with clear milestones and full transparency.

01

Audit

We perform a deep technical audit of your ML infrastructure: serving stack, pipelines, monitoring, and reproducibility posture.

02

Architect

We design a targeted optimization plan with clear milestones, technology choices, and expected outcomes. No fluff.

03

Deploy & Hand Off

We implement everything, run load tests, set up alerting, and transfer full ownership to your team with documentation.

Core Technologies

PyTorchTensorFlowTensorRTONNXTriton Inference ServerKServeKubernetesDockerMLflowKubeflowOpenTelemetryRay ServeFastAPIGrafana

Ready to scale your AI?

Let's talk about your ML infrastructure. We'll identify the biggest bottlenecks and show you exactly how to fix them, for free.

Serving clients across EMEA · UAE · India