DoiT gave us the confidence to move from experimentation to production. They helped us understand the right way to build AI for the real world.
Milad Rezazadeh, CTO
Recommendations don't cut costs. Execution does.
Cloud Intelligence™ detects, decides, and executes optimizations across AWS, Google Cloud, and Azure, with Forward Deployed Engineers embedded in your team. Book a 30-minute demo and see your savings potential live.
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Trusted by 3,500+ cloud-driven organizations
you can't just "tag" a customer
How It Works
Attribute’s eBPF and Deep Packet Inspection (DPI) tech allows us to scan and identify customers’ identifiers from the traffic and correlate cloud consumption in runtime.
- eBPF-based data extraction.
- Automatically identify costs from real-time usage.
- Runtime cost distribution across all customer accounts.
- No change in code or configuration
What they say
Attribute™'s cost grouping technology took our cost visibility and allocation to a whole new level. Now, our teams are fully accountable for their budgets, significantly improving our cloud efficiency and helping us minimize unnecessary costs.
Eli Zilbershtein, Head of DevOps, Hippo
You can't tag a customer in a multi-tenant environment. Attribute™ finally shows us what each customer costs and what's driving those costs.
Omri Cohen, Director of Engineering, Platform
Attribute™'s data is truly unmatched. No other solution on the market could deliver the precise customer cost and usage profiles we needed in such a complex infrastructure. Within weeks, the data from Attribute™ transformed our understanding of cost structures, influencing key strategic decisions in pricing, renegotiations, and market positioning.
Jonathan Langer, COO, Claroty
Attribute™ simplified tracking customer costs in our multi-tenant environments. Customer cost measurement is now clear and standardized, and finance gets the business context they need. Integration was quick and required no changes.
Kfir Lippmann, CFO, Salt Security
Attribute™ translates complex cloud bills into actionable, business-centric insights that empower our engineering teams to take true ownership of their costs.
Balamurugan Mohandossgandhi, Head of IT and Infrastructure, PropertyGuru
This has let us get a better idea of what our cost of goods sold really is. It's not every day you come across something that delivers value as quickly as yours did for us. I was seeing useful insights inside the POC, and we had only deployed it to a couple of real clusters.
Jason Moore, Principal DevOps Engineer, Accrete AI
Eliminating the need to tag thousands of resources has freed up my team and we've invested our efforts in enhancing our platform significantly.
Ziv Sivan, VP of Engineering
what you get
Cloud Intelligence™ sees what your tools miss
LLM gateways, shared GPU clusters, and AI agents don't have tags. They never will. Instead, we read runtime network traffic directly, identifying which model was called, by which workload, triggered by which customer or agent.
Token-in, token-out
Input, output, and cached tokens broken out per request.
Allocate AI cost per feature
See which product features drive LLM spend.
Per-agent cost
Measure what each AI agent costs to run.
AI anomalies. In real-time.
Catch unexpected token spikes before they hit margins.
AI usage per customer, human vs. non-human
Separate human spend from agent and know what each customer actually costs to serve.
Signals → actions
Pause keys or swap models when usage crosses policy.
AI-driven Kubernetes automation for peak efficiency.
Self-Optimizing Kubernetes Infrastructure
Cut Kubernetes costs by up to 50% and improve reliability with real-time, workload-aware automation for production environments.
PerfectScale uses AI-driven insights to analyze dynamic usage patterns, determine the right resource levels for your workloads, and eliminate misconfigurations, ensuring optimal performance and consistent availability across your infrastructure.
save 20% on Snowflake, Databricks or BigQuery. Automatically.
Optimization and query-level visibility for Snowflake, Databricks, and BigQuery.
Warehouse utilization optimization runs continuously. No manual intervention required. Teams using PerfectScale typically see double-digit compute savings within the first two weeks across Snowflake, Databricks, and BigQuery.
stop leaving money on the table
Automate AWS, GCP and Azure commitments
Risk-aware automation with built-in execution controls gives you full oversight while capturing more savings across AWS, Google Cloud, and Azure. No guesswork. No overcommitment. No regrets.
