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CIFL

Project consultancy · Cloud · AI infrastructure

Infrastructure for what comes next.

CIFL Consult advises on and manages the cloud, platform, and AI infrastructure programs that ambitious companies depend on.

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Conceptual topology · not a live system

Capability signature

  • AWS
  • Google Cloud
  • Microsoft Azure
  • Kubernetes
  • Terraform
  • Docker
  • GitHub Actions
  • OpenTelemetry
  • Prometheus
  • Grafana

The infrastructure layer

Your product moves fast.
Your infrastructure program should too.

Modern products depend on increasingly complex infrastructure. Cloud platforms, distributed systems, Kubernetes, databases, GPUs, AI models, CI/CD pipelines, observability, and security all have to work together.

CIFL Consult turns that complexity into programs your engineering team can actually govern and deliver.

Reference path

Services

Project consultancy across the infrastructure stack.

All capabilities →

Solutions

Programs for companies where infrastructure is a competitive advantage.

  1. 01

    AI companies

    Inference, GPU capacity, and serving programs that can survive production traffic.

  2. 02

    SaaS platforms

    Multi-tenant cloud architecture, delivery pipelines, and reliability programs.

  3. 03

    Growing startups

    The simplest architecture that will carry the next stage — without premature platforms.

  4. 04

    Enterprises

    Migration, landing-zone, and modernization programs with explicit governance.

Cloud programs

One consulting mindset.
Every major cloud.

AWS, Google Cloud, and Microsoft Azure are different control planes. The program — landing zones, networking, security, delivery — should still be coherent.

Discuss the architecture
AWSGCPAzure

CIFL architecture layer

Program governance · advisory

NetworkingComputeContainersDatabasesStorageSecurityObservabilityAutomation

Platform & DevOps

From commit to production,
without the chaos.

Automated infrastructure is predictable infrastructure. We advise on the delivery program — IaC, CI/CD, GitOps, environment promotion — so changes are reviewable and repeatable.

  • Terraform
  • Kubernetes
  • Docker
  • GitHub Actions
  • Argo CD
  • GitOps

AI infrastructure

Intelligence needs infrastructure.

Running AI in production isn't only about the model. It's about GPUs, scheduling, throughput, latency, utilization, scaling, networking, observability, and cost. Metrics below are illustrative — a picture of the control plane a program should have, not live production data.

  1. GPU CLUSTER
  2. Scheduler
  3. Inference Engine
  4. Model
  5. API
  6. Users

GPU UTILIZATION

87%

Illustrative

TOKENS / SEC

1,842

Illustrative

P95 LATENCY

142 ms

Illustrative

COST / REQUEST

$0.004

Illustrative

Plan AI infrastructure

Observability

If you can't see it,
you can't improve it.

Reliability programs need a control plane: CPU, memory, latency, requests, errors, GPU utilization, and deployment events — in one place, owned by the team that ships.

Control plane · illustrative

Live view

CPU
Memory
Latency
Requests

Errors

0.12%

GPU utilization

74%

Deployment events

  • 14:02 Deploy api-gateway@sha-9c2
  • 14:11 Autoscaler +2 replicas
  • 14:18 Error budget 2.1% remaining

Cloud economics

Cloud should scale your business.
Not your bill.

FinOps is a program: attribution, rightsizing, GPU governance, and architecture review. We do not invent savings percentages.

Before

  • Overprovisioned compute
  • Idle GPUs
  • Unoptimized workloads
  • Manual infrastructure

CIFL optimization

  • Rightsizing
  • Autoscaling
  • Architecture improvements
  • GPU utilization
  • FinOps

After

  • Lower infrastructure waste
  • Better utilization
  • Predictable scaling

Approach

Engineering with intent.

  1. 01

    Understand

    Workload, product, constraints, architecture, business goals.

  2. 02

    Architect

    Design the simplest architecture capable of supporting the required scale.

  3. 03

    Plan

    Infrastructure as Code, CI/CD, security, testing, and delivery governance.

  4. 04

    Assure

    Observe, optimize, secure, and continuously improve — as advisory, not operations.

Why CIFL

Not another cloud vendor.

CIFL Consult operates as a project management consultancy and engineering advisor. Licensed for project management consultancy — not as a managed cloud operator.

  1. Engineering over configuration

    We don’t simply provision services. We advise on systems.

  2. Automation over manual work

    Infrastructure should be reproducible, version-controlled, and observable.

  3. Outcomes over complexity

    The best architecture is not the most complicated one. It’s the one that solves the problem reliably.

CIFL Architecture Lab

Explore a conceptual architecture.

Hover or focus a component to highlight connections, the role it plays, and related technologies. This is a blueprint for discussion — not a prescribed stack.

Selected work

Illustrative engagements

Placeholder program types. No customer names, logos, or invented metrics.

Illustrative

AI inference platform

GPU infrastructure designed for scalable model serving.

Challenge
A product team needed an inference path with explicit latency, utilization, and cost controls.
Architecture
Dedicated serving tier, GPU scheduling policy, and an observability contract from queue to token.
Program
Advisory on topology, capacity planning, and a delivery program the internal team could own.
Outcome
A governed inference program with reviewable changes — not an outsourced operations contract.

Illustrative

Cloud-native SaaS

Highly available cloud architecture and automated deployment platform.

Challenge
Growth had outpaced a single-environment delivery path and informal failover.
Architecture
Landing-zone patterns, environment promotion, and a reliability review for the data plane.
Program
Program management of the migration sequence, IaC standards, and CI/CD governance.
Outcome
A reproducible platform program with a clear owner inside the customer’s engineering org.

Illustrative

Infrastructure modernization

Legacy infrastructure transformed into reproducible cloud environments.

Challenge
Manual environments made change risky and recovery untested.
Architecture
The simplest cloud architecture that preserved required isolation and recovery objectives.
Program
Phased modernization with architecture review, IaC, and a rehearsal of failover.
Outcome
Environments that can be rebuilt from source, with economics and risk made explicit.

Insights

Thinking beyond the infrastructure diagram.

All writing →

About

Infrastructure is a program, not a purchase.

CIFL exists to help technology companies build infrastructure that is reliable enough to disappear into the background. We combine cloud, DevOps, platform, reliability, and AI infrastructure expertise as project management consultancy — so complex programs stay governable.

About CIFL →

Let's plan what comes next.

Tell us what you're building, where your infrastructure program is struggling, or what you're trying to scale.

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