Finout launches world-first FinOps integration to track OpenAI Codex spend in dollars. Quick summary. Finout has launched the first AI FinOps integration for OpenAI Codex, allowing enterprises to convert credit-based billing into real-time dollar metrics. This solution enables engineering and finance teams to allocate AI spend by team, product, and cost center, ensuring total visibility across complex agentic workflows. How does Finout solve OpenAI Codex billing complexity? Finout addresses the challenge of credit-based billing attribution by automatically converting OpenAI Codex Enterprise credits into actual dollar amounts based on a company's specific contract rate. As enterprise Codex adoption surged from 0% to 17% in less than a year, the need for granular visibility has become critical for budgeting and forecasting. * Automated credit conversion at custom contract rates. * Granular cost slicing by user, model, and reasoning effort. * Unified billing layer via MegaBill to consolidate AI and cloud costs. What results has Finout anomaly detection delivered? By extending real-time anomaly detection to Codex, Finout prevents massive budget overruns caused by shifts in AI reasoning tiers. A team moving from medium to high reasoning effort can multiply costs overnight; Finout identifies these spikes immediately. This proactive approach ensures unit economics remain stable even as AI usage scales across the organization. * Instant alerts on reasoning-effort cost multipliers. * Three-month backfill of usage data upon initial connection. * Plain-English queries via Billy, the AI FinOps assistant. "Connecting OpenAI Codex inside Finout finally let us allocate AI spend by team and improve our ROI projections instead of guessing at them" said the Head of FinOps at a Large B2B SaaS company. How does Finout ensure data security and privacy? The integration is strictly read-only and secure, accessing only usage and credit metadata without ever touching prompt or code content. This ensures that enterprise intellectual property remains protected while providing the financial transparency required by leadership. The platform maintains SOC 2 Type II and ISO 27001 certifications to meet global compliance standards. Ff news take: This move by Finout significantly moves the needle because it treats AI FinOps integration as a core financial pillar rather than a side project. As coding agents become the default enterprise workflow, the ability to map AI unit economics directly to business outcomes is no longer optional. Finout is successfully positioning itself as the essential connective tissue between generative AI adoption and corporate fiscal responsibility. Banking license authorization

Finout has launched Finout Agents, a suite of three AI-powered agents designed to autonomously detect, investigate and remediate cloud cost issues for enterprise FinOps teams. The system aims to expand FinOps team capacity by 10 times without increasing headcount. The suite comprises three agents: the Detector Agent monitors for anomalies, the Investigator Agent traces issues to root cause whilst cross-referencing ownership and deployment records, and the Orchestrator Agent executes fixes automatically or routes them to appropriate owners via Slack or Jira. The agents operate on MegaBill, Finout's patented unified data layer consolidating spend across AWS, Azure, GCP, Kubernetes, and AI services including OpenAI and Anthropic. CEO Roi Ravhon said the system addresses FinOps' capacity bottleneck rather than data availability issues.

Israel-based Finout has raised $40 million in a Series C funding round led by Insight Partners, with participation from Pitango, Team8, Red Dot Capital and Maor Investments. The investment brings the company's total funding to $85 million. Finout provides a cloud-agnostic cost allocation and governance platform for enterprises, serving clients including SiriusXM, Lyft, The New York Times and Wiz. The company's FinOps platform offers visibility and control over cloud spending through advanced allocation, unit economics analysis and forecasting capabilities. The funding will support new enterprise features, including financial planning tools, instant virtual tagging for cost allocation and tagging governance features. The investment reflects growing demand for sophisticated cloud cost management solutions as organisations grapple with rising cloud complexity and AI investments.