400+ ways to
cut your cloud bill.
PointFive's DeepWaste™ Detection Engine finds cloud waste that no other tool can — from quick wins to deep architectural inefficiencies — across AWS, Azure, GCP, OCI, Snowflake, Databricks, Kubernetes, and AI platforms. Our baseline identifies 15–30% waste reduction, and customers usually find significantly more.
Most tools only scratch the surface.
PointFive categorizes every finding into five layers of depth — from common resource waste to deep architectural inefficiencies. At every layer, validated detection, rich context, and engineering-ready remediation turn findings into real savings.
Orphaned, inactive, and abandoned resources still incurring charges. Most tools flag some of these — but accurate identification across millions of resources requires validated detection, dependency mapping, and engineering-ready remediation to actually turn findings into savings.
Misaligned settings versus real usage — storage tiers, disk types, capacity modes, instance sizes, and caching configurations. Validating these at scale demands correlation of performance metrics, usage patterns, and workload context to produce recommendations engineers actually trust and act on.
Waste created by how applications use cloud services — API call patterns, model selection, transfer routing. Invisible without deep application-level analysis and multi-source data correlation.
Data that has aged out of its original purpose but stays in expensive storage tiers. Retention policies that no longer reflect actual access patterns. Requires continuous monitoring of data access frequency and intelligent lifecycle recommendations.
Suboptimal infrastructure design causing structural cost overhead — routing decisions, region placement, cluster sizing. Requires VPC Flow Logs, snapshot side-scanning, and virtual cost allocation techniques unique to PointFive. The hardest to find, often the most impactful to fix.
Every layer matters. Every layer compounds.
Real savings come from continuous detection across all five layers — with validated context, root-cause analysis, and engineering-grade remediation at every depth. Surface findings fund the deeper work. Deeper layers prevent waste from recurring.
Increasing detection depth
What sets PointFive apart isn't just finding waste — it's the validated context, multi-source correlation, and remediation tooling that turns findings into action across every layer. Deeper layers require VPC Flow Logs, snapshot side-scanning, and virtual cost allocation — techniques unique to PointFive.
Comprehensive Coverage
The broadest and deepest coverage.
DeepWaste analyzes 85+ cloud and AI services across all major providers, with new services added continuously.
85+
Cloud & AI Services Analyzed
Compute
5 services
Kubernetes
9 services
Databases
13 services
AI & ML
10 services
Data & Analytics
6 services
Storage
11 services
Serverless
4 services
Networking
9 services
Observability
7 services
Streaming
7 services
Security
4 services
optimizations.
A curated sample of what our DeepWaste™ engine detects — each backed by usage patterns, configuration analysis, and validated remediation playbooks. The real catalog runs much deeper.
Expensive VPC NAT Gateway Deployment
AWSDetects workloads routing massive data through NAT Gateways when free alternatives like Gateway Endpoints exist. A single endpoint deployment can eliminate hundreds of thousands in annual data processing fees.
Schedulable EC2 Instances
AWSIdentifies instances with low off-hours activity that can be automatically started and stopped on a schedule. Eliminates waste from resources running 24/7 when only needed during business hours.
Serverless-Ready OpenSearch Domains
AWSIdentifies low-usage provisioned OpenSearch domains that are candidates for serverless migration — eliminating fixed instance costs for intermittent workloads.
Suboptimal Azure Disk Types
AzureUniversal detection across all Azure managed disk types — Premium SSD, Standard SSD, and Standard HDD — identifying disks that can be downtierred based on actual IOPS and throughput patterns.
GPU Instance Rightsizing
AWSIdentifies GPU instances (P4d, P5, G5, Inf2) running ML training and inference workloads at low GPU utilization — recommending smaller instance types or spot-based alternatives without impacting throughput.
Vertex AI Training Job Optimization
GCPDetects Vertex AI custom training jobs using oversized machine types or running without preemptible/spot instances — common in ML experimentation workflows where cost discipline is often overlooked.
Showing 6 of 10 detections in this category. Want to see what's hiding in your infrastructure?
Real customer impact
Example customer achieved full ROI in 10 days. Another saved $600K from a single NAT Gateway endpoint deployment. Our average customer ROI exceeds 500% — and the real number? You wouldn't believe it.
avg ROI
These are just samples.
Run a free Proof of Value on your own cloud environment and see exactly which of the 400+ detections apply to your infrastructure — with dollar amounts attached.
Fixing it is the whole point.
Every optimization includes engineering-grade remediation — from AI coding agents that generate contextual fixes to built-in workflow integrations that keep your team moving. Detection without action is just a report. PointFive delivers outcomes.
AI Coding Agents
Every finding ships with contextual, engineering-ready remediation — generated by AI coding agents that understand your infrastructure, not generic templates.
Built-In Workflows
Connect directly to Jira, Slack, ServiceNow, and your existing ticketing systems. Findings flow into your team's natural workflow — no context switching required.
Infrastructure-as-Code
Terraform and CloudFormation fixes ready to merge. Every remediation maps to your IaC stack — so changes go through your existing review and deploy pipeline.
Human Oversight at Every Step
Root-cause analysis, impact assessment, and safe rollback paths — all included. AI generates the fix. Your engineers review, approve, and deploy with full confidence.
From finding to fix in minutes, not months.
Traditional cost optimization ends with a spreadsheet. PointFive delivers validated findings with actionable remediation — so engineering teams ship savings instead of triaging alerts.
Deep analysis on every one.
Not just visibility — DeepWaste™ analyzes usage patterns, access frequencies, and workload characteristics across 90+ services organized by infrastructure domain.
Detects different.
Agentless architecture
The only agentless Kubernetes optimization solution on the market. Read-only access, zero deployment overhead, minutes to first insight.
Research-driven detection
A dedicated Cloud Cost Research Team ships ~10 new optimization types weekly — using methodologies inspired by cybersecurity threat intelligence.
Multi-source data correlation
We don't just read your bill. We correlate billing data with CloudWatch metrics, VPC Flow Logs, CloudTrail activity, and direct API state — finding waste that single-source tools miss.
Agentic Remediation
AI coding agents deliver contextual recommendations with human-curated remediation playbooks. Every opportunity includes root cause analysis, impact assessment, and engineering-grade execution paths—with full human oversight at every step.
See what you're
missing today.
Get a free assessment of your cloud waste. Most customers find 15–30% savings within the first week.
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