As enterprises scale AI and analytics workloads, cloud and data platform costs are rising at unprecedented rates. "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," said Sharon Gross, Vice President of Product at PointFive.
To help organizations address these growing costs, PointFive has expanded its Cloud and AI Efficiency Platform to support Snowflake, Databricks, and BigQuery, building on its existing coverage of AWS, Azure, and GCP. The expansion provides enterprises with the visibility and tools they need to detect inefficiencies, prioritize savings opportunities, and optimize both cloud infrastructure and data platforms without disrupting operations.
Data platforms are increasingly critical to enterprise AI and analytics, but they can also be a major source of hidden waste. Oversized compute clusters, unused tables, redundant pipelines, and misaligned storage often go unnoticed, quietly inflating cloud spend. PointFive's DeepWaste™ detection engine analyzes both infrastructure and platform usage, surfacing more than 400 potential savings opportunities with full technical context.
This approach helps teams focus on the highest-value opportunities, turning wasted resources into funds for AI initiatives, innovation, or overall cost reduction.
PointFive delivers targeted, actionable insights for each major data platform:
Snowflake: Right-size warehouses, remove pipelines feeding unused tables, and reduce storage bloat from Time Travel and FailSafe.
Databricks: Optimize cluster configurations and scaling for workload requirements, while eliminating unused tables and volumes.
BigQuery: Detect reservation waste, optimize slot commitments, and remove jobs feeding outdated or unused datasets.
These recommendations reach deep into pipelines, compute, query patterns, and storage layers, uncovering inefficiencies that traditional monitoring tools often miss.
PointFive doesn't stop at detection. AI-assisted, agentic workflows turn insights into remediation quickly. Suggested fixes are delivered as Infrastructure-as-Code, run locally, and include human approval steps, ensuring teams retain full control over changes.
Integration with agentic IDEs such as Cursor and Windsurf, along with collaboration platforms like Slack, Jira, and ServiceNow, allows teams to implement remediation without switching tools or contexts. Every action is tracked to actual financial impact, providing transparency into the savings achieved.
PointFive operates in a metadata-only, read-only mode, giving enterprises comprehensive insights without touching production workloads or introducing governance risk. Query text analysis is optional, and metadata collection runs on isolated compute resources. Dedicated service accounts with strictly read-only permissions maintain full control while enabling deep, safe optimization.
The platform's expansion is powered by InfraFabric, PointFive's continuous cloud and infrastructure data fabric. InfraFabric maps cost, usage, telemetry, ownership, and system dependencies into a living model of the entire environment.
PointFive's AI assistant, Pointer, leverages this context to provide plain-language insights: which workloads are driving unnecessary spend, who owns them, potential savings, and how remediation can be applied. AI Co-Workers continuously monitor environments, surface opportunities, and route actions to the right teams within governance guardrails.
By extending optimization to Snowflake, Databricks, and BigQuery, PointFive enables enterprises to embed efficiency as an ongoing practice. Organizations can uncover hidden waste, streamline remediation, and reclaim resources to reinvest in AI, innovation, or other strategic initiatives.
Enterprises interested in seeing how PointFive can optimize their cloud and data platforms can book a demo to explore the platform in action.