Cloud adoption continues to accelerate as organizations invest heavily in AI and data-driven innovation. Yet alongside this growth comes a new operational challenge: the rapid rise of data platform costs. As companies rely more heavily on tools that power analytics and AI pipelines, inefficiencies hidden deep within data infrastructure can quietly inflate cloud bills. PointFive is addressing this issue with a new expansion of its Cloud and AI Efficiency Platform, adding support for Snowflake, Databricks, and BigQuery.
The expansion extends PointFive’s optimization capabilities beyond the core cloud providers AWS, Azure, and GCP, enabling organizations to manage efficiency across both infrastructure and the data platforms that increasingly drive modern workloads.
Tackling a Fast-Growing Source of Cloud Spend
Data platforms have become one of the fastest-growing categories of cloud spending. PointFive’s latest move targets what it describes as a multi-billion-dollar opportunity in data platform misconfiguration and inefficiency.
By unifying cloud infrastructure and data platforms into a single system, the platform enables teams to identify waste and prioritize the most impactful savings opportunities. The company’s DeepWaste™ detection engine surfaces more than 400 potential areas for optimization and highlights where inefficiencies exist across the environment.
This visibility enables teams to reclaim spending that might otherwise go unnoticed. Those savings can be redirected toward AI initiatives, innovation projects, or broader efforts to reduce total cloud costs.
Optimization Across the Data Stack
PointFive’s expansion focuses on improving efficiency across the most widely used enterprise data platforms.
In Snowflake environments, the platform identifies opportunities to right-size warehouses, remove pipelines feeding unused tables, and reduce storage bloat caused by Time Travel and FailSafe features.
For Databricks, the system evaluates cluster configurations and scaling behavior to ensure they match workload requirements while also identifying unused tables and volumes.
Within BigQuery environments, PointFive detects reservation waste, recommends adjustments to slot commitments, and identifies jobs that feed outdated or unused data assets.
The goal is to uncover inefficiencies that often remain hidden inside query patterns, data pipelines, compute layers, and storage usage.
From Detection to Remediation
Finding waste is only part of the equation. PointFive also focuses on helping teams resolve issues quickly through agentic remediation workflows.
Once inefficiencies are identified, the platform generates AI-assisted remediation suggestions delivered as Infrastructure-as-Code. These fixes run locally and include human approval flows so that teams retain full control over changes.
Remediation can integrate directly with existing development and collaboration tools, including agentic IDEs such as Cursor and Windsurf, as well as platforms like Slack, Jira, and ServiceNow. Each action is tracked against measurable financial outcomes so teams can clearly see the savings generated.
Built With Enterprise Security in Mind
The platform is designed to operate without introducing governance risk or disrupting production systems. PointFive works in a metadata-only and read-only model, allowing organizations to analyze optimization opportunities without interacting directly with workloads.
Query text analysis is optional, and metadata collection runs on isolated compute resources that do not affect production performance. Dedicated service accounts maintain strictly read-only permissions, allowing enterprises to maintain full control over their environments.
Intelligence That Connects the Entire Environment
The new data platform capabilities are powered by InfraFabric, PointFive’s cloud and infrastructure data fabric. InfraFabric continuously maps cost, usage, telemetry, ownership, and system dependencies, creating a living model of the organization’s full environment.
This model allows PointFive’s AI assistant, Pointer, to answer questions about potential savings with full context. Instead of returning dashboards or requiring technical queries, the assistant explains which workloads are driving unnecessary spending, which teams own them, and what remediation could look like.
AI Co-Workers extend this capability further by continuously monitoring environments, surfacing optimization opportunities, and routing actions to the appropriate teams within established governance guardrails.
Turning Optimization Into a Continuous Practice
For many enterprises, cloud efficiency efforts remain reactive and fragmented across different teams and tools. PointFive aims to change that by treating optimization as an ongoing operational practice that spans infrastructure and data platforms.
"PointFive now brings continuous, context-powered optimization to the platforms where some of the most significant and fastest-growing cloud spend lives. The same intelligence, the same results — across the complete stack."
Organizations interested in exploring how the platform works can book a demo to see how PointFive identifies inefficiencies and helps teams capture measurable savings across their cloud and data environments.