Cloud-native infrastructure at enterprise scale

Your Cloud Bill Grows. Your Team Burns Out. Your Competitors Ship Faster.

50+ cloud engineers. AI-native infrastructure — not DevOps retooled. Outcome-priced engagements on AWS, Azure, and GCP so you stop fighting your infrastructure and start outrunning the market.

74%

74% of organizations are seeing AI create value, but only for roughly 20% of companies at meaningful scale.

PwC Global AI Jobs Barometer, 2026
2.5×

Reinvention-ready companies grow revenue 2.5 times faster than their peers.

Accenture Technology Vision, 2025
88%

88% of organizations are now using AI in at least one business function.

McKinsey State of AI, 2025
18%

Only 18% of companies have AI meaningfully embedded into their core workflows.

Harvard Business Review, 2026

Registered partner on the world's three leading cloud platforms

Microsoft Solutions Partner
Google Cloud Partner
AWS Partner Network

Our engineers hold accreditations and certifications across all three platforms

The Cloud Problem Is Real

The numbers that explain why your cloud ops feel broken

20–30%

EBITDA uplift from full cloud transformation

McKinsey
90%

of engineers use AI tools — yet most see little ops improvement

DORA
Up to 70%

of cloud spend wasted on idle or oversized resources

Gartner
$250k/hr

average cost of unplanned enterprise infrastructure downtime

IDC

The Problem We Solve

What's holding your cloud operations back

What's Holding You Back

Runaway cloud costs with no FinOps governance
Alert fatigue and on-call burnout from reactive ops
Slow, high-risk deployment cycles blocking the business
Compliance and security gaps in infrastructure

What Needs to Change

FinOps-governed spend with real-time cost visibility
Self-healing systems that fix themselves before customers notice
Policy-as-code CI/CD enabling sub-hour release cycles
Zero-Trust IaC with embedded compliance controls

Our Approach

How We Fix It

We don't retool DevOps engineers with AI scripts and call it transformation. We build AI-native infrastructure from the ground up — self-healing, cost-governed, and enterprise-compliant.

  • Platform Engineering & Internal Developer Platforms
  • AIOps — predictive monitoring and autonomous remediation
  • MLOps — model CI/CD and production infrastructure
  • FinOps — cloud cost governance and rightsizing
  • Zero-Trust Infrastructure as Code
  • Multi-cloud migrations and landing zones
50+

Cloud and DevOps Engineers

Cloud infrastructure, SRE, platform, and DevOps specialists across AWS, Azure, and GCP.

3

Cloud Platforms

Registered partner on AWS, Azure, and GCP

6 wks

Avg. time-to-value

From kickoff to production infrastructure

Who Does the Work

The Specialist Roles Behind Every Engagement

Senior-only practitioners across six cloud disciplines — deployed in the combination your platform requires.

Principal / Staff

Cloud Architect

Designs multi-cloud landing zones, governance frameworks, and network topology across AWS, Azure, and GCP.

  • Landing zone design
  • Multi-cloud architecture
  • FinOps governance
  • Compliance blueprints
Senior / Staff

Site Reliability Engineer

Owns reliability targets, error budgets, and incident response automation — eliminating on-call burnout through self-healing systems.

  • SLO / SLA definition
  • On-call automation
  • Runbook elimination
  • Capacity planning
Senior / Staff

Platform Engineer

Builds internal developer platforms that let product teams ship independently — CI/CD pipelines, golden paths, and toolchain standardisation.

  • Internal dev platforms
  • CI/CD pipelines
  • Golden-path templates
  • Developer portals
Senior / Staff

MLOps Engineer

Operationalises AI models at scale — from experiment tracking and model registries to production inference infrastructure.

  • Model CI/CD
  • Experiment tracking
  • Feature stores
  • Inference infra
Senior

FinOps Analyst

Governs cloud spend through real-time cost allocation, rightsizing recommendations, and reserved capacity optimisation.

  • Cost allocation
  • Rightsizing analysis
  • Reserved capacity
  • Showback / chargeback
Senior / Staff

Security Engineer

Embeds Zero-Trust controls and policy-as-code into every pipeline — so compliance is continuous, not a pre-audit scramble.

  • Zero-Trust IaC
  • Policy-as-code
  • CSPM / CNAPP
  • Compliance automation

Not sure which roles your engagement needs? We'll scope it with you.

Our Technology Stack

What We Use

Five purpose-built technology pillars — every tool is production-tested and compliance-auditable.

Hover any card to reveal details

Technology Stack

Cloud and platform technologies we work with

Technology selection adapts to your existing cloud estate, team conventions, and compliance posture.

AWSCloud
AzureCloud
Google CloudCloud
KubernetesOrchestration
TerraformInfrastructure
DockerContainers
GrafanaMonitoring
PrometheusMonitoring
DatadogMonitoring
OpenTelemetryObservability
SentryObservability
GitHubSource Control
JenkinsCI/CD
PythonBackend

Technology selection is guided by client environment, existing investments, and engineering requirements. This list is not exhaustive.

Why CodeCones — Not a Typical Cloud Provider

Most cloud service firms are DevOps shops with AI painted on top. We built for AI-native operations from the start.

Cloud Partner Certified Engineers

  • Accredited on AWS, Azure, and Google Cloud
  • Specializations in AI and cloud-native platforms
  • Partner-tier technical access and roadmap previews

Cloud Partner Accreditations

Microsoft Solutions PartnerGoogle Cloud PartnerAWS Partner Network

Registered partner on AWS, Azure, and Google Cloud Platform.

Enterprise Security Controls

  • ISO 27001 Information Security — audit-ready
  • ISO 9001 Quality Management — structured delivery
  • Documented data handling and incident response

Outcomes Driven Engineering Delivery

  • Every engagement starts with the business outcome
  • Delivery through launch, documentation, and handover
  • Aligned to your timelines and constraints

The research case for AI-native cloud operations

20–30%

EBITDA improvement from full cloud transformation

McKinseyCloud's Trillion-Dollar Prize
90%

of technology professionals now use AI at work

DORAState of AI-Assisted Dev
35–45%

faster software delivery with AI-assisted engineering

McKinseyEconomic Potential of Gen AI

After CodeCones

What changes across industries

Platform engineering outcomes are business outcomes. Before and after, by vertical.

Financial Services

Before

Banking and financial-services workflows often depend on fragmented customer information, manual coordination, complex approval processes, and disconnected service systems.

After

McKinsey reports that banks rewiring selected frontline domains with agentic AI have seen 3% to 15% higher revenue per relationship manager and 20% to 40% lower cost to serve.

Improved access to customer context

Reduced manual coordination

This is third-party research concerning selected banking frontline domains and is not a CodeCones customer result or guaranteed outcome.

Healthcare

Before

Revenue-cycle operations often span payer, provider, billing, document, patient-service, and finance systems. Manual exception handling can increase administrative effort and slow resolution.

After

McKinsey estimates that AI enablement of healthcare revenue-cycle operations could reduce cost to collect by 30% to 60%.

Lower manual administrative effort

Faster exception handling

This is a third-party industry estimate and is not a CodeCones customer result or guaranteed outcome.

Technology / SaaS

Before

Faster code generation does not automatically improve product delivery when testing, deployment, data access, security, and operational processes remain fragmented.

After

DORA reports that 90% of technology professionals use AI at work, while more than 80% perceive that it has increased their productivity.

More controlled AI adoption

Better delivery-system visibility

This is third-party industry research and is not a CodeCones customer result or guaranteed productivity improvement.

Manufacturing

Before

Maintenance information is often fragmented across equipment, telemetry, work-order, inventory, and manual reporting systems.

After

McKinsey reports that predictive maintenance can reduce machine downtime by 30% to 50% and increase machine life by 20% to 40%.

Earlier detection of equipment risk

Reduced unplanned operational disruption

This is a third-party industry benchmark and is not a CodeCones customer result or guaranteed outcome.

FAQs

Cloud & Platform Engineering — Frequently Asked Questions

DevOps focuses on culture, practices, and tooling that bridge development and operations — CI/CD pipelines, release automation, and shared ownership of reliability. Platform Engineering builds the internal developer platform that teams use to deploy and operate their services independently. Both are related, and most mature engineering organisations need elements of both. We design the right combination for your context.

We design multi-cloud environments around workload fit, governance requirements, existing investments, and risk tolerance — not vendor preference. We hold accreditations across AWS, Azure, and GCP and design landing zones, network topology, and governance frameworks that give you real portability without unnecessary complexity.

AIOps uses machine learning and analytics to improve IT operations — predicting incidents before they become outages, automatically correlating alerts across systems, and recommending or executing remediation actions. In practice it means self-healing infrastructure that reduces on-call burden and prevents customer-visible failures rather than just reacting to them.

FinOps governance is built into our cloud architecture from the start. We implement real-time cost allocation by team, product, and environment, rightsizing recommendations backed by utilisation data, reserved capacity strategies, and showback or chargeback reporting. Cloud cost visibility is a monitoring requirement, not an afterthought.

Zero-Trust IaC means that security policy is written as code and enforced at every layer of the infrastructure — network, identity, workload, and data. No implicit trust based on network location. Policy-as-code is checked in CI pipelines so compliance failures are caught before deployment, not discovered in post-deployment audits.

Ready to Start

Ready to Stop Fighting Your Infrastructure?

Talk to one of our cloud engineers. We'll review your current estate, identify the highest-impact opportunities, and outline a time-to-value path — no commitment required.

Cloud & Platform Engineering Insights

Get in Touch

Tell us about your infrastructure goals

Our cloud engineers will respond within one business day with a practical assessment — not a sales pitch.

  • Dedicated project manager from day one
  • Fixed-scope or continuous engagement options
  • Full IP ownership — all deliverables are yours
  • Response within one business day

No commitment required. We typically respond within one business day.