Cloud AI Optimization and Finops Consulting

Find the money your AI workflows are wasting.

AI is the fastest-growing and least scrutinized line on your AWS bill. As leading Cloud Optimization Specialists we not only streamline your AI Workloads, we optimize the rest of your Cloud Spend too. Read-only, in your own account, reporting the same day.

Book a walkthrough → What we find
100% read-only
5 min to deploy
Nothing leaves your account
$0
avg / mo identified · sample accounts
0
automated FinOps checks
0 min
to your first report
0%
read-only access

What we find

Generic cost tools don't look at AI spend. We do.

Two layers in every report: the AI & ML section on top and the full FinOps baseline underneath.

// where we lead

AI & ML optimization

The fastest-growing line on your bill, finally scrutinized.

  • SageMaker endpoint utilization & idle detection
  • GPU generation and rightsizing
  • Spot-for-training and real-time vs. async serving
  • Bedrock commitment analysis & model-choice arbitrage

// the value floor

The FinOps baseline

The config-change tier alone usually pays for the exercise the first month.

  • Idle & previous-generation EC2, Savings Plan coverage
  • NAT gateway and cross-AZ transfer bleed
  • Unattached storage, stale snapshots, gp2 migration
  • Idle RDS & load balancers, S3 lifecycle, log retention

Services

Consulting scoped from our findings and validated against your own bill.

The report gets you the numbers. You choose where we help.

AI & ML cost optimization

Idle GPU endpoints, training that belongs on Spot Fleets, frontier-priced models doing small-model work, Bedrock spend past the commitment breakeven.

FinOps baseline

The full general sweep: idle and previous-gen compute, commitment coverage, transfer topology, storage and lifecycle, log retention.

Architecture engagements

Re-platforming inference, data-transfer topology that's scoped, evidence-backed, and only where you want it.

How it runs

Deployed in your account. No egress. Reporting the same day.

Your security team signs off because there's nothing to sign off on, every permission is a Describe/List/Get call.

STEP 01

Deploy

Drop a CloudFormation or Terraform template into your account. About five minutes of hands-on time.

STEP 02

Analyze

A read-only Lambda inventories the account and runs the full check catalog AI first, baseline underneath.

STEP 03

Report

A ranked savings report lands in your own S3 bucket with built-in dashboard, PDF, and machine-readable findings.

Sample reports

Representative accounts: every figure a labeled estimate with evidence behind it.

Open any of them in full — read the sample reports →

AI-heavy startup

$6,373/mo

GPU endpoints billing around the clock, Bedrock past breakeven, training that belongs on Spot.

21 findings · 1 account

Data-platform org

$5,576/mo

Two-account organization, and cross-AZ transfer topology and SageMaker utilization.

13 findings · 2 accounts

Lift-and-shift enterprise

$2,821/mo

No AI at all is the value floor. Idle compute, coverage gaps, storage and lifecycle.

18 findings · 1 account

Our tooling

Tools we build, running read-only inside your own account.

Two analyzers, one deployment model: a read-only stack you install in your own account. No SaaS backend, no agents, no data egress. Unless you want it.

Available

Cost & AI spend

CloudAI FinOps Essentials

A one-page AWS savings report: a single estimated-monthly-savings figure up front, every finding ranked by dollars and tagged by remediation effort. AI & ML on top, the full FinOps baseline underneath, delivered as a dashboard, PDF, and findings file in your own bucket. Multi-account AWS Organization support.

Read a sample report →
19 checks · SageMaker, Bedrock, GPU, EC2, RDS, S3, network Output · dashboard, PDF, findings.json Deploy · CloudFormation or Terraform · read-only

In development

Security posture

Bulwark

Posture management for AWS, built the same way: every finding names the control it fails and carries the evidence that proves it, so nothing lands on your queue that you cannot verify. Misconfiguration coverage is running today; identity exposure and workload vulnerabilities are the next two pillars.

Ask about early access →
29 checks · S3, IAM, EC2/VPC, RDS, KMS, logging Output · findings envelope, control reference per finding Next · identity entitlements (CIEM), workload CVEs

New analyzers appear here as they ship.

Who you work with

Cloud economists and architects. Real People, not just a dashboard.

Placeholder profiles — swap in real names, roles, and photos before launch.

Pierce Blunt

Founder · Lead Cloud Economist · Lead Solutions Architect

Pierce is a leading expert in AI on AWS, specializing in Amazon SageMaker, Amazon Bedrock, and AI workload optimization. Holding every current active AWS certification and backed by experience delivering solutions for Fortune 500 companies, Pierce helps organizations right-size their AI infrastructure to maximize performance while minimizing costs.

Ian Cates

Lead FinOps Consultant · Lead Data Architect

Ian is our Lead Data Architect and FinOps Consultant, specializing in designing scalable data architectures and high-performance data pipelines. With deep expertise in enterprise-scale AI platforms and FinOps practices, Ian helps organizations build efficient, reliable, and cost-optimized data ecosystems that power advanced analytics and AI initiatives.

Jack Wilkinson

Director of Client Outreach · Lead Solutions Consultant

Jack Wilkinson is our Director of Client Outreach and Lead Solutions Consultant. With a consultative approach and a strong understanding of cloud, data, and AI solutions, Jack works with organizations to identify business needs, develop tailored strategies, and deliver technology solutions that drive measurable results. He is focused on building trusted client relationships and ensuring successful outcomes throughout every engagement.

Next step

A 30-minute walkthrough of a sample report for your architecture.

Then the template for a report on your own account. Or just send a note — we read every one.