DoiT
Procurement partnerAbout
DoiT builds Cloud Intelligence™, a FinOps platform that uses a patent-pending eBPF sensor to allocate 100% of cloud spend to customers, teams, and features without requiring resource tagging. The platform covers cost visibility, anomaly detection, Kubernetes optimization, and FinOps automation across AWS, Google Cloud, Azure, Oracle Cloud, and 40+ other providers. DoiT also provides Forward Deployed Engineers — senior cloud architects embedded with customer teams — alongside professional service...
Details
VenSearch Intelligence
Ideal Customer
- DoiT's sweet spot is the mid-market to enterprise digital-native or cloud-native company — typically a fast-growing SaaS business, technology startup, or enterprise with significant and complex multi-cloud spending across AWS, Google Cloud, and/or Azure.
- The platform is positioned for engineering, finance, and FinOps teams at companies that have outgrown native cloud billing tools but need more automation and expert support than pure-software FinOps tools provide.
Key Differentiators
- DoiT positions itself as the only 'intent-aware' FinOps platform — meaning it evaluates cloud spend in the context of what each workload is actually supposed to do, not just whether costs rose.
- It was named a Visionary in the September 2025 Gartner® Magic Quadrant™ for Cloud Financial Management Tools, recognized for its Completeness of Vision and Ability to Execute.
Industries Served
- DoiT's primary focus is on digital-native, cloud-driven technology companies, with the heaviest concentration in Information Technology & Services (23% of reviewers) and Computer Software (16%), according to Capterra user data.
- The platform is used across Financial Services (5%), as well as SaaS, e-commerce, fintech, and insurtech verticals — evidenced by a partnership with Tenity, an accelerator for fintech and insurtech startups.
Service Coverage
- DoiT operates globally, serving customers across more than 70 countries with a fully remote-first team.
- The company is headquartered in Santa Clara, California, and has legal entities registered in the United States and the United Kingdom, with historical offices in Israel (Tel Aviv), Australia, and across European markets including the UK, France, Germany, Benelux, Nordic countries, Ireland, Spain, and Portugal.
Partnerships
- DoiT holds top-tier status with all three major hyperscalers: AWS Premier Tier Services Partner (with 500+ AWS certifications and six AWS competencies including MSP, Migration, Data Analytics, DevOps, SaaS, and Well-Architected), Google Cloud Premier Partner (and an 8x Google Cloud Partner of the Year), and Microsoft Gold Solutions Partner.
- In November 2025, DoiT announced a major strategic alliance with Ingram Micro to bring DoiT Cloud Intelligence to 5,000+ Ingram Micro AWS partners and 12,000 downstream customers, with planned integration into Ingram Micro's Xvantage platform.
Company Size & Ownership
- DoiT was founded in 2011 by Vadim Solovey and Yoav Toussia-Cohen and is headquartered in Santa Clara, California, with a globally distributed remote workforce.
- Employee counts vary across sources, but the most recent figures place headcount in the 700–800 range (approximately 697–789 employees as of 2025–2026).
Compliance & Certifications
- DoiT holds SOC 2 Type II and SOC 3 certifications, which are audited annually by an independent third party evaluating security, availability, confidentiality, and privacy controls.
- The company is also certified under ISO/IEC 27001:2022 for its information security management system, and maintains GDPR, CCPA, EU-US Data Privacy Framework, and ICO Registered compliance.
Compiled from public sources by VenSearch · Last researched October 14, 2026
Offerings
27 offeringsAI Hub
AI Hub tracks the cost of every AI task by team, user, repository, and initiative across 16+ AI connectors including Claude, ChatGPT Enterprise, Cursor, Amazon Bedrock, and more. It introduces Taskonomics, which groups AI usage into task types such as coding, debugging, and agentic workflows, then measures cost per solved task. It also includes an AI gateway, model governance controls, and per-user spending limits without requiring SDK changes.
Allocations
Allocations is a Cloud Intelligence product feature that splits cloud cost by customer or team. It provides unified cost allocation across cloud environments to give organizations control over how spend is divided and reported.
Anthropic Practice
The Anthropic Practice is a professional services offering that helps organizations build production-grade agentic systems using Anthropic's Claude models. It is designed to take AI projects from experimentation to production-ready deployment.
Attribute Per Customer (Per-Customer)
Attribute Per Customer uses a lightweight eBPF sensor to read customer identifiers from runtime traffic and attribute 100% of cloud spend — including shared Kubernetes clusters, databases, network egress, and LLM tokens — to individual customers without tagging or code changes. Each customer account receives a cost-to-serve, COGS line, and gross margin figure, with human and agent usage split. Underpriced accounts are flagged automatically before renewal.
AWS AI Assessment
The AWS AI Assessment is a consulting engagement that takes an organization from AI ambition to a concrete AI roadmap on AWS. It evaluates current capabilities and defines a structured path to production AI deployment on AWS infrastructure.
Benchmarks
Benchmarks allows organizations to compare their FinOps performance and cloud spending efficiency against peer companies of similar size. It provides context for whether AI spend, cost trends, and optimization maturity are in line with industry norms.
Claude on Bedrock Accelerator
The Claude on Bedrock Accelerator is a professional services offering that helps organizations migrate their Claude AI workloads to Amazon Bedrock. It is designed to move existing Claude implementations to AWS-managed infrastructure.
Cloud Diagrams
Cloud Diagrams provides up-to-date architecture visualization of cloud environments. It is listed as a product feature within the Cloud Intelligence platform that shows live maps of resource connections.
CloudFlow
CloudFlow is a FinOps automation engine inside Cloud Intelligence that turns savings recommendations, anomaly alerts, and governance policies into no-code automated workflows that run on schedules or event triggers across AWS, Google Cloud, Azure, and Oracle Cloud. It includes 50+ ready-made flow templates built by Forward Deployed Engineers for tasks like cleaning up idle resources, enforcing tag policies, and migrating EBS volumes. Approval steps can be inserted before any risky action, and every run is logged with a full change history.
Cost & Usage
Cost & Usage provides unified cost visibility across 40+ cloud and SaaS providers in a single view. It consolidates billing data from all connected cloud environments to support FinOps reporting and analysis.
FinOps Practice
The FinOps Practice solution is designed to help organizations build a mature, automation-driven FinOps function and eradicate the 'Illusion of Efficiency' — where reported savings don't reflect actual cost reduction. It combines Cloud Intelligence software with expert guidance to systematize cost governance and optimization.
FinOps without Tagging
FinOps without Tagging is a solution that uses Cloud Intelligence's runtime attribution technology to allocate 100% of cloud spend from day one without requiring a tagging program. It addresses the industry reality that even mature tagging programs cover only 43% of cloud cost at the unit level, with shared infrastructure, network, and AI remaining untagged.
Forward Deployed Engineering
Forward Deployed Engineering embeds senior cloud architects directly within customer engineering teams to identify and implement real fixes to cloud cost and architecture problems. Rather than delivering reports or recommendations, Forward Deployed Engineers work alongside customers to cut costs, optimize architecture, and ship production-ready changes. The service covers cost reduction, Kubernetes optimization, BigQuery tuning, and AI workload architecture.
From Data to Insights Accelerator
The From Data to Insights Accelerator is a professional services engagement that helps organizations build a modern data platform. It covers architecture design and implementation to enable data-driven decision-making at scale.
GenAI Accelerator
The GenAI Accelerator is an engagement designed to help companies ship production-ready AI products. It accelerates the path from AI experimentation to live, scalable AI features in production environments.
Headless FinOps
Headless FinOps enables AI agents to act as the user interface for FinOps operations within Cloud Intelligence. It allows automated agents to query, analyze, and act on cloud cost data programmatically without human-driven dashboard interaction.
Insights
Insights runs 800+ proprietary checks against a customer's real cloud environment across five pillars — cost, security, performance, reliability, and operations — using a proprietary engine called Composer that understands resource relationships, ownership, and usage history. Unlike provider recommendations that judge resources in isolation, Composer knows whether a resource is production, who owns it, and what depends on it before surfacing a finding. Savings estimates are based on actual billing data, and findings can be actioned directly via CloudFlow, Terraform PRs, or Jira/Linear tickets.
MSPs and Distributors Solution
DoiT offers a solution tailored to Managed Service Providers and distributors to help them optimize and scale their cloud businesses using Cloud Intelligence. It is designed to help MSPs deliver FinOps capabilities to their own customers.
OpenAI Practice
The OpenAI Practice is a professional services offering that helps organizations build production-grade agentic systems using OpenAI models. Like the Anthropic Practice, it focuses on moving AI workloads from proof-of-concept to production.
PerfectScale for Commitments
PerfectScale for Commitments automates rate optimization for cloud commitment instruments such as Reserved Instances and Savings Plans. It is designed to reduce the manual effort required to manage commitment coverage and maximize discount rates.
PerfectScale for Data Platforms
PerfectScale for Data Platforms rightsizes and optimizes data cloud environments such as Snowflake and Databricks. It provides cost intelligence and optimization specifically focused on data platform spending.
PerfectScale for Kubernetes
PerfectScale for Kubernetes rightsizes Kubernetes clusters in real time through autonomous optimization, keeping cluster costs low while maintaining performance. It eliminates the need for engineering teams to manually monitor and adjust Kubernetes resource configurations.
Procurement Advisory
Procurement Advisory is a consulting service that helps organizations purchase cloud services more effectively. It is described as a smarter way to buy cloud, guiding procurement decisions to optimize contract terms and spending.
Real-time Anomaly Detection
Real-time Anomaly Detection monitors cloud, data platform, and AI provider spend and alerts within minutes of a cost spike, identifying the customer, team, or feature that drove it along with an AI-generated root cause and suggested next step. It covers AWS, Google Cloud, Azure, Oracle Cloud, Snowflake, Databricks, Datadog, OpenAI, Anthropic, ClickHouse Cloud, Cloudflare, Cursor, Elastic Cloud, GitHub, Grafana Cloud, and Vercel. Alerts are routed to Slack, Microsoft Teams, or email by severity level, and can automatically trigger CloudFlow automations.
Showback & Chargeback
Showback and Chargeback allocates shared cloud infrastructure costs — including Kubernetes clusters, databases, NAT gateways, and AI spend — to the team or workload that actually consumed them using runtime observation via an eBPF sensor. This replaces pro-rated or even-split allocation methods that engineering and finance teams frequently dispute. Every cost spike is routed to the owning team with the cause attached.
Unit Economics
Unit Economics maps cloud spend to business metrics — such as cost per customer, per ride, per transaction, or per AI inference — by reading runtime traffic via an eBPF sensor, eliminating the need for tagging, data pipelines, or spreadsheets. The sensor attributes shared infrastructure costs including Kubernetes clusters, network egress, databases, and LLM tokens to the specific business unit that consumed them. Teams can track unit cost trends over time, measure elasticity, and connect engineering decisions directly to gross margin.
Venture & Private Equity Solution
DoiT provides a solution for venture capital and private equity firms to optimize cloud spending across their portfolio companies. It extends Cloud Intelligence visibility and optimization capabilities to multi-company investment portfolios.
Considering DoiT?
Our team will work with you to determine if DoiT is the right fit for your organization. From research and assessment through procurement negotiation and ongoing vendor management — we handle the entire process at no cost to you.