Products at a glance

www.doit.com names 15 products under DoiT.

  • Attribute Every AI Token to the Customer, Feature, and Agent Behind It — AI spend is a black box. LLM Gateways show token totals but can’t tell you who burned them. Attribute traces every token, inference, and training run back.
  • Attributed at Runtime — Allocate cloud spend by team, service, or environment with fallback logic and shared cost splitting across AWS, Azure, and Google Cloud.
  • Catch spikes in minutes — Detect cloud cost spikes within minutes across AWS, Google Cloud, and Azure. DoiT delivers context-rich alerts with AI-powered root cause analysis and…
  • Chargeback & Showback — Allocate shared cloud costs by team using real runtime usage, not tags or spreadsheets. Accurate chargeback and showback in one CLI line. Book a demo.
  • Data clouds optimization. — Automated cost visibility and optimization for Snowflake, Databricks, and BigQuery. Reduce compute spend by 10-20% with PerfectScale for Data Lakes.
  • Find what your provider can't. Fix it on your terms. — Composer is the intelligence engine inside Cloud Intelligence™. 700+ rules continuously run against your real multi-cloud data.
  • FinOps on autopilot — Turn FinOps recommendations into automated multi-cloud workflows. Schedule resources, right-size workloads, and clean up idle spend without writing code.
  • From alert, to root cause, to pull request. — Stop manually triangulating incidents across tools. Agentic AI correlates signals, diagnoses root cause, and opens a PR with the fix — inside Slack and GitHub.
  • Get fluent in your costs — Translate your public cloud bill into language your business understands. Unified visibility across AWS, Azure, and Google Cloud with no pipelines or prep work.
  • Kubernetes optimization with added reliability. — Autonomous Kubernetes optimization with full visibility. Rightsize clusters, track GPU utilization, and align DevOps and FinOps in a single platform.
  • No more guesswork. — Risk-aware commitment automation with guardrails. Manage AWS Savings Plans, Database Savings Plans, and GCP CUDs in one system. No overcommitment.
  • True per-Customer Costs — Attribute’s eBPF deep packet inspection captures every signal, calculating cost-to-serve based on consumption data.
  • Unit Economics — Measure cloud cost per customer, feature, or AI call with an eBPF sensor. No tagging, no pipelines. Deploy in 15 minutes and see unit economics this week.
  • Visualize your cloud infrastructure in real time — Get live infrastructure maps with cost data, dependency tracking, and AI-powered queries across AWS and Google Cloud.
  • Your agents are the UI — FinOps as REST, MCP, and CLI. Run cost analytics, anomalies, commitments, and FDE workflows from any agent or terminal. No dashboard required.

Sources: Attribute AI | Cloud Intelligence™, Cloud Cost Allocation | Cloud Intelligence™, Real-Time Cloud Cost Anomaly Detection | DoiT, Cloud Cost Chargeback & Showback by Team | Attribute, Data Platforms Optimized - Snowflake, Databricks, BigQuer, Insights | Cloud Intelligence™, CloudFlow | Next Gen FinOps Automation | Cloud Intelligence™, Agentic Cloud Operations | Cloud Intelligence™, Cloud Analytics | Multi-cloud Cost Visibility | DoiT, PerfectScale for Kubernetes | Cloud Intelligence™, PerfectScale for Commitments | Cloud Savings | DoiT, Attribute Per Customer | Cloud Intelligence™

Attribute Every AI Token to the Customer, Feature, and Agent Behind It

AI spend is a black box. LLM Gateways show token totals but can’t tell you who burned them. Attribute traces every token, inference, and training run back. The page “Attribute AI | Cloud Intelligence™” on www.doit.com records: Attribute AI without Attribute Every AI Token to the Customer, Feature, and Agent Behind It AI spend is a black box. LLM Gateways show token totals but can’t tell you who burned them. Attribute™ traces every token, inference, and training run back to the team, product, and customer that drove it. True AI TCO, across every provider.

Source: Attribute AI | Cloud Intelligence™

Attributed at Runtime

Allocate cloud spend by team, service, or environment with fallback logic and shared cost splitting across AWS, Azure, and Google Cloud. The page “Cloud Cost Allocation | Cloud Intelligence™” on www.doit.com records: Attributed at Runtime See a demo Most tools read your billing exports. We read runtime telemetry and map costs to the workloads that incurred them. Everything your team needs to see. Know which team, customer, or feature is driving your AI spend.

Source: Cloud Cost Allocation | Cloud Intelligence™

Catch spikes in minutes

Detect cloud cost spikes within minutes across AWS, Google Cloud, and Azure. DoiT delivers context-rich alerts with AI-powered root cause analysis and severity scoring. The page “Real-Time Cloud Cost Anomaly Detection | DoiT” on www.doit.com records: Catch spikes in minutes Book a demo Get alerts within minutes of any unusual usage patterns, including full business context - what customer, team or feature drove it. Fast-growing companies run on Cloud Intelligence™ real-time, not retroactive What makes this different Most FinOps tools detect anomalies hours or days late.

Source: Real-Time Cloud Cost Anomaly Detection | DoiT

Chargeback & Showback

Allocate shared cloud costs by team using real runtime usage, not tags or spreadsheets. Accurate chargeback and showback in one CLI line. Book a demo. The page “Cloud Cost Chargeback & Showback by Team | Attribute” on www.doit.com records: See the true cost of every Chargeback & Showback Cloud cost chargeback that actually works. Know the true TCO of every team based on actual usage, not guestimations or spreadsheets work. Trusted by teams shipping AI in production every customer. automatically.

Source: Cloud Cost Chargeback & Showback by Team | Attribute

Data clouds optimization.

Automated cost visibility and optimization for Snowflake, Databricks, and BigQuery. Reduce compute spend by 10-20% with PerfectScale for Data Lakes. The page “Data Platforms Optimized - Snowflake, Databricks, BigQuer” on www.doit.com records: Data clouds optimization. Book a demo Start free trial → Optimization and query-level visibility for Snowflake, Databricks, and BigQuery. why teams switch PerfectScale for Data Platforms Real-time monitoring and automated optimization so teams can quickly understand where spend is happening, how workloads are performing, and where meaningful savings can be captured.

Source: Data Platforms Optimized - Snowflake, Databricks, BigQuer

Find what your provider can't. Fix it on your terms.

Composer is the intelligence engine inside Cloud Intelligence™. 700+ rules continuously run against your real multi-cloud data. The page “Insights | Cloud Intelligence™” on www.doit.com records: Find what your provider can't. Fix it on your terms. Book a demo Prioritized, actionable insights across cost, security, performance, reliability, and operations. Built from your real environment and context. bespoke to your environment Your environment is bespoke. Your insights should be too.

Source: Insights | Cloud Intelligence™

FinOps on autopilot

Turn FinOps recommendations into automated multi-cloud workflows. Schedule resources, right-size workloads, and clean up idle spend without writing code. The page “CloudFlow | Next Gen FinOps Automation | Cloud Intelligence™” on www.doit.com records: FinOps on autopilot Book demo Act on savings recommendations, resource scheduling, idle resources. Automatically. Automations Build workflows that scale with your business Cloud operations is never one size fits all. You’re in control. Automate even the most complex FinOps or SRE workflows with our powerful, intelligent automation engine.

Source: CloudFlow | Next Gen FinOps Automation | Cloud Intelligence™

From alert, to root cause, to pull request.

Stop manually triangulating incidents across tools. Agentic AI correlates signals, diagnoses root cause, and opens a PR with the fix — inside Slack and GitHub. The page “Agentic Cloud Operations | Cloud Intelligence™” on www.doit.com records: From alert, to root cause, to pull request. Book a demo Correlate signals across cloud, observability, security, and deployment tools, diagnoses root cause, maps blast radius, and proposes the fix in Slack and GitHub. Zero permanent access No Permanent Write Access. Ever. Giving an AI agent permanent write access to production is a terrible idea. We agree.

Source: Agentic Cloud Operations | Cloud Intelligence™

Get fluent in your costs

Translate your public cloud bill into language your business understands. Unified visibility across AWS, Azure, and Google Cloud with no pipelines or prep work. The page “Cloud Analytics | Multi-cloud Cost Visibility | DoiT” on www.doit.com records: Get fluent in your costs See a demo Translate your public cloud bill into language your business understands. How it works One platform, every cloud, zero prep work Cloud Analytics ingests billing data from AWS, Azure, and Google Cloud. It normalizes usage, enriches it with business context, and makes it explorable from high-level trends to line-item details.

Source: Cloud Analytics | Multi-cloud Cost Visibility | DoiT

Kubernetes optimization with added reliability.

Autonomous Kubernetes optimization with full visibility. Rightsize clusters, track GPU utilization, and align DevOps and FinOps in a single platform. The page “PerfectScale for Kubernetes | Cloud Intelligence™” on www.doit.com records: Kubernetes optimization with added reliability. Free savings analysis Reduce AWS EKS and GCP GKE costs by up to 50% with workload-aware automation. Trusted by platform engineering teams Two products, one platform What PerfectScale for Kubernetes delivers PerfectScale provides autonomous optimization while Kubernetes Lens gives you preconfigured dashboards inside Cloud Intelligence™.

Source: PerfectScale for Kubernetes | Cloud Intelligence™

No more guesswork.

Risk-aware commitment automation with guardrails. Manage AWS Savings Plans, Database Savings Plans, and GCP CUDs in one system. No overcommitment. The page “PerfectScale for Commitments | Cloud Savings | DoiT” on www.doit.com records: No more guesswork. Free savings analysis Automatic optimization for AWS, Azure, and Google Cloud with reduced risk of commitment lock-in and no overcommitments. stop leaving money on the table PerfectScale™ for 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.

Source: PerfectScale for Commitments | Cloud Savings | DoiT

Sources

  1. Attribute AI | Cloud Intelligence™ https://www.doit.com/products/attribute Verified 19 Sep 2026
  2. Attribute Per Customer | Cloud Intelligence™ https://www.doit.com/products/attribute-per-customer Verified 19 Sep 2026
  3. Cloud Cost Chargeback & Showback by Team | Attribute https://www.doit.com/products/attribute-chargeback Verified 19 Sep 2026
  4. CloudFlow | Next Gen FinOps Automation | Cloud Intelligence™ https://www.doit.com/products/cloudflow Verified 19 Sep 2026
  5. Real-Time Cloud Cost Anomaly Detection | DoiT https://www.doit.com/products/real-time-anomalies Verified 19 Sep 2026
  6. Insights | Cloud Intelligence™ https://www.doit.com/products/insights Verified 19 Sep 2026
  7. Cloud Cost Allocation | Cloud Intelligence™ https://www.doit.com/products/allocation Verified 19 Sep 2026
  8. Cloud Analytics | Multi-cloud Cost Visibility | DoiT https://www.doit.com/products/cloud-usage-cost Verified 19 Sep 2026
  9. PerfectScale for Commitments | Cloud Savings | DoiT https://www.doit.com/products/perfectscale-for-commitments Verified 19 Sep 2026
  10. PerfectScale for Kubernetes | Cloud Intelligence™ https://www.doit.com/products/perfectscale-for-kubernetes Verified 19 Sep 2026
  11. Data Platforms Optimized - Snowflake, Databricks, BigQuer https://www.doit.com/products/perfectscale-for-data-platforms Verified 19 Sep 2026
  12. Agentic Cloud Operations | Cloud Intelligence™ https://www.doit.com/products/agentic-cloud-operations Verified 19 Sep 2026

Last verified 20 Aug 2026. This entry is compiled from the public web pages listed above. Nothing here is stated that those pages do not, and each of them was read on the date shown.