Krylox
ServicesProcessGPU HostingBlogMLOps MaturityGet Started
MLOps & Inference Optimization

Your AI in production.
Fast, cost-efficient, and drift-proof.

Krylox engineers MLOps pipelines and optimizes inference, then hosts your models on our own GPU fleet, billed by the day.

MLOps assessmentSee what we do
Team experience from
GoogleMetaBloomberg
10×
Faster Inference
60%
Cost Reduction
3
Big Tech Practitioners
24/7
Pipeline Monitoring
What We Do

Specialist MLOps engineering.
Every layer of the production stack.

01Inference Optimization
02MLOps Pipeline Design
Core Service

Inference Optimization

Your models leave latency on the table. We recover it through quantization, pruning, kernel fusion, and intelligent batching.

INT8/FP16 quantization with TensorRT and ONNX
Kernel fusion and operator optimization
Dynamic batching and request queuing
Latency profiling and bottleneck elimination
GPU utilization analysis and tuning
Core Service

MLOps Pipeline Design

CI/CD built for ML. Automated training, evaluation, versioning, and deployment pipelines so your models stay current and your team stays focused on building.

Feature store design and integration
Automated retraining triggers and canary deploys
OpenTelemetry observability across the pipeline
KServe / Triton serving infrastructure
Kubeflow and Airflow orchestration
Monitoring

Drift Protection

Keep your model drift-proof in production. Live statistical monitoring, prediction logging, and automated retraining loops catch degradation before it reaches your users.

Real-time data and concept drift detection
Automated model validation pipelines
Prediction quality dashboards with alerting
Zero-human retraining and redeployment
Infrastructure

Reproducibility Systems

A model that only runs on one MacBook quietly becomes dead code the moment a data scientist leaves. We kill that risk on day one.

Immutable container builds and environment pinning
MLflow registry with full artifact versioning
Experiment tracking and comparison tooling
Exact dependency management across environments
Cost Engineering

Cloud Cost Optimization

Right-sizing, spot instance strategies, and serving architecture tuning that cuts monthly GPU bills by up to 60%.

Spot instance and preemptible GPU strategies
Workload right-sizing and instance selection
Model compression to reduce serving footprint
Multi-cloud and hybrid deployment architectures
Managed Infrastructure

Managed GPU Hosting

Deploy your optimized model on Krylox's own GPU fleet. Plans start from a single day, auto-scaling built in, 99.9% uptime SLA included.

Flexible billing, from as low as per day
Krylox-managed GPU infrastructure
Auto-scaling to match your traffic
99.9% uptime SLA with live monitoring
Fully managed updates, patching, and security
Works with any optimized model we deliver
The Reality

Most production failures
aren't technical.

Zillow lost $500M, not because of bad code, but because a market moved while the model stood still. The gap between research and reliable production is a strategy problem, not a syntax problem.

Krylox closes that gap. The same practices that run ML at Google and Meta, applied to your stack.

“It works on my machine” is a strategy failure waiting to happen.
What we deploy by default
Live statistical drift monitoring, always on
Automated retraining, no human in the loop
Immutable containers, survives people, laptops, time
Full observability: traces, logs, prediction metrics
Canary deploys with automatic rollback
Why Krylox

What separates us
from generalist agencies.

01
Rare specialization

MLOps and inference optimization is a narrow, technically demanding domain. Most agencies don't go near it.

02
Big tech pedigree

Google, Meta, Bloomberg. We've shipped ML infrastructure at scale. Same standards, smaller team, more attention.

03
Your cloud. Your model.

BYOC and BYOM, we deploy within your AWS, GCP, or Azure environment, or host on our own GPU fleet. We optimize whatever framework you're running. No migration required.

04
Zero vendor lock-in

Every system we build uses open standards. No proprietary wrappers, no mandatory subscriptions, no dependencies that require us to stay involved. You own the code and the pipeline.

05
Results, measured

Every engagement begins with a baseline and ends with measured results. Up to 10× inference improvement and up to 60% cost reduction, grounded in benchmarks and our team's production experience.

06
Full ownership transfer

Every engagement ends with complete documentation, team walkthroughs, and runbooks. We measure success by how little you need us after we leave.

How We Work

From audit
to live production.

Phase 01
01
Discovery Audit

We profile your stack, latency, cost, and pipeline bottlenecks, then tell you exactly what to fix first and what it's worth.

Phase 02
02
Strategy & Roadmap

A prioritized technical plan: tooling decisions, milestones, and cost-benefit analysis. You know exactly what we're building and why.

Phase 03
03
Implementation

Krylox owns and executes the full technical build — optimisation, automation, monitoring setup. Your team provides context, access, and feedback. We do the engineering.

Phase 04
04
Handover & Support

Full documentation, team walkthroughs, and runbooks. You own the system completely, with the confidence to run it independently.

Managed GPU Hosting

Your model. Our GPUs.
You pay for what you use.

No reserved instances. Deploy your optimized model on Krylox infrastructure, plans start from a single day.

01
Optimize your model

We compress and optimize your model for maximum throughput on our GPU fleet, up to 10× faster than a naive deployment.

02
Deploy to Krylox infrastructure

Your model runs on our managed GPU fleet with auto-scaling, load balancing, and 99.9% uptime SLA, all handled by Krylox.

03
Call your endpoint. Pay per use.

A simple REST or gRPC endpoint. Plans start from a single day, pay only for what you use, no surprise bills.

Why host with Krylox
Zero cloud overhead

No AWS/GCP accounts, IAM roles, VPCs, or reserved instances to manage. We handle all infrastructure operations.

Cost-efficient at any scale

Plans start from a single day. No contracts to renegotiate, no capacity to reserve upfront.

Optimized hardware

Our fleet is tuned for ML inference, not general compute. Your model runs on hardware selected and configured specifically for it.

99.9% uptime SLA

Live monitoring, automatic failover, and Krylox on-call for any incident. Production reliability is our responsibility.

Get a hosting quote →
Tech Stack

The tools in our production stack.

Frameworks
PyTorchTensorFlowJAXONNXOpenVINO
Serving
TensorRTvLLMTriton Inference ServerKServeRay ServeBentoML
MLOps
MLflowWeights & BiasesDVCKubeflowAirflowPrefect
Cloud
AWS SageMakerGCP Vertex AIAzure MLKubernetesDocker
Monitoring
PrometheusGrafanaEvidently AIArizeOpenTelemetry
FAQ

What clients ask before engaging.

Krylox LLP is a specialist MLOps and AI inference optimization engineering firm. We help technical startups and enterprises ship ML models that are fast, cost-efficient, and reliable in production, handling everything from pipeline design to live drift monitoring. We also host models on our own GPU fleet.

No. We operate on BYOC (Bring Your Own Cloud) and BYOM (Bring Your Own Model) principles. We deploy within your existing AWS, GCP, or Azure environment and optimize whatever framework you're running, PyTorch, TensorFlow, JAX, or fine-tuned LLMs.

A discovery audit takes approximately 2 weeks and delivers a full optimization roadmap. A full implementation, pipeline build, inference optimization, monitoring setup, typically runs 4 to 6 weeks. Embedded engineering engagements are flexible and ongoing.

Yes, completely. Every system we build uses open standards with no proprietary dependencies. You receive full source code, documentation, runbooks, and team walkthroughs. We measure success by how little you need us after we leave.

Krylox operates globally with active clients across EMEA, UAE, India, and the United States. We work across time zones without friction.

Send us a message

Let's talk.

Share your stack, pain points, and goals. We'll reply within 24 hours.

Email
hello@krylox.ai
Availability
EMEA · UAE · India · US
Response time
Within 24 hours

We respond within 24 hours with a specific recommendation, not a sales pitch.