Meet Anavsan’s agentic AI that prevents Snowflake credit loss at the source and drives up to 50% cost savings.
The Problem: The Hidden Cost of Scale in Snowflake
Anavsan is an agentic AI platform that stops Snowflake credit loss at its root, guarantees up to 50% cost savings via actionable insights and automation, and drastically reduces manual effort for data and FinOps teams.
For Data Engineers and FinOps Executives, the power of Snowflake's elastic scale often comes with a significant, unpredictable cost: Credit Loss. As data teams scale workloads, credits leak through a maze of inefficiencies: oversized warehouses, forgotten Time Travel settings, expensive query anti-patterns, and unused tables.
Traditional Snowflake cost optimization tools offer dashboards for cost monitoring but they leave the burden of analysis, risk-assessment, and fixing entirely to the data team, slowing innovation. The source of the cost problems starts with inefficient queries and difficulty in achieving a fine balance between required performance and reducing cost.
Anavsan: Agentic AI Platform for FinOps and Collaborative Optimization of Snowflake
We built Anavsan to change that.
We are thrilled to announce the launch of Anavsan for Snowflake, the first agentic AI platform designed to tackle cost optimization in Snowflake by fixing credit loss at the source while simultaneously helping teams to achieve the best query performance. Anavsan doesn't just monitor; it analyzes, predicts, monitors, simulates, and guides your team to execute the most impactful, risk-free savings opportunities.
Anavsan reads only metadata and query information, ensuring your data remains secure within your Snowflake environment. All the data are encrypted with 256-bit encryption inflight and at rest.
Anavsan acts as a continuous AI assistant, moving beyond generic rules. It constantly analyzes your Snowflake metadata, logs, and query history, including database usage, storage growth, and compute consumption.
The differentiator is the Company-Specific Knowledge Graph. By understanding your environment's structure, priorities, and best practices for Snowflake optimization, Anavsan's AI assistant delivers recommendations and changed queries that are not just accurate, but contextual—ensuring performance is never sacrificed for savings. This is true Snowflake data warehouse optimization.
Pillar 1: Fix Snowflake Credit Loss at the Source with Context
The biggest barrier to deep Snowflake cost optimization is risk. Will reducing the retention time on a large table break compliance? Will rightsizing a warehouse hurt performance?
Anavsan introduces the Simulation Engine, a unique feature that lets teams simulate credit savings and query performance before making any changes without ever wasting your Snowflake credits. Users can test the impact of adjustments—from right-sizing workloads and tuning queries to optimizing Snowflake storage cost optimization settings—with zero risk. This gives data leaders the confidence to validate actions and prioritize the highest value optimizations, moving straight toward Snowflake cost savings.
Cost control is a team sport. Anavsan closes the gap between FinOps, engineering, analysis, and architecture with a collaborative workspace.
- For FinOps: pinpoint the slow, failing, or expensive query creating credit loss and assign it for remediation, including the user who can resolve it.
- For engineers: receive the assignment with historical context, AI-driven recommendations, and predicted savings impact.
Pillar 2: Eliminate risk with the Simulation Engine
This feature accelerates performance improvements and provides an auditable process. Teams can simulate credit savings and query performance before making changes, without spending Snowflake credits.
Pillar 3: The collaborative FinOps and data teams workspace
The workspace is how cost control becomes a shared workflow instead of a Slack thread and a spreadsheet.
Why Anavsan delivers better Snowflake cost optimization
Compared with traditional monitoring tools:
- Traditional tools alert you after credits are spent. Anavsan analyzes continuously to prevent credit loss at the source.
- Traditional tools provide visibility and still require manual work. Anavsan provides contextual recommendations and action guidance.
- Traditional optimization changes are a guess. The Simulation Engine tests impact before production.
- Traditional tools require external communication between teams. Anavsan unifies FinOps and data teams for faster resolution.
You can start a trial at agent.anavsan.com/signup. Anavsan reads only metadata and query information. Data stays in your Snowflake environment and is encrypted in flight and at rest.
Unleash the potential of your Snowflake warehouse without uncontrolled credit loss.
See how Anavsan governs your Snowflake costs
APEX detects cost anomalies, assigns them to the owning engineer, and documents savings with proof — automatically.