FinOpsly
The Unified FinOps Platform Built for the AI Era

AI adoption is accelerating across every industry, and enterprises are racing to modernize the systems that support it. They are re-architecting and shifting massive workloads across cloud (AWS, Azure) and data platforms (Snowflake, Databricks) while layering AI and generative AI services on top of already complex environments. But innovation now costs money by the minute. Every server spun up, data query, and each model training run adds to a growing bill that soon balloons beyond visibility. Those bills eventually land on a CIO’s desk as separate invoices with no way to connect spending to teams, products or projects, turning efficiency into guesswork.

FinOpsly enters at this exact breaking point. Built on the two foundational ideas of unification and agentic automation, it is the first AI-native and enterprise-grade predictive cost control system for optimizing cloud, data, and AI costs at scale. Its platform uncovers inefficiencies, removes waste across idle and oversized resources, and keeps enterprise infrastructure in a cost-healthy state.

“Point solutions do not work in the world we operate in now. Enterprises need unification and agentic automation to survive the scale of cloud and AI. We bring that clarity in one platform,” says Kiran Jain, CEO.

The unification is brought to life in the FinOpsly platform through four connected pillars called spend analytics, spend optimization, financial operations, and spend planning.

On the analytics front, FinOpsly’s Ask FI conversational interface gives leaders instant, natural language clarity into spend. A simple question like “How much did we spend on compute last quarter” returns a full business dimension view of consumption across teams, products and environments.

Point solutions do not work in the world we operate in now. Enterprises need unification and agentic automation to survive the scale of cloud and AI. We bring that clarity in one platform.

Optimization builds on this intelligence. The platform scans millions of cloud and data resources and uncovers the drains that inflate budgets. Unused instances, overprovisioned machines, forgotten snapshots and stale storage all surface with context. Through agentic automation, copilot guides engineers through safe corrective actions, and autopilot handles repeatable cleanups on its own. The result is continuous, automated cost improvement without slowing engineering momentum.

“Innovation velocity with cloud and AI is accelerating exponentially,” says Lathika Hegde, FinOpsly’s CTO and Co-Founder. “While enterprises focus on building differentiated features and products, FinOpsly provides engineers time to focus on high-value work while FI agents silently identify and act on savings opportunities.”

The financial operations module brings structure and fairness. Chargebacks reflect real usage, not rough allocations, and the platform supports automated cost allocation with zero tag dependency. Shared costs can be distributed with precision. Forecasts become credible because they draw from live operational data. Finance and engineering gain a shared view of spend, which reduces friction and turns cost decisions into a collaborative process.

Spend planning completes the system. This is where Costix steps in. Teams can describe the application they want to build, and Costix automatically generates an architecture blueprint and a reliable, context-aware cost estimate. It is the first of its kind solution in the FinOps market that gives enterprises proactive planning, solutioning and estimation across cloud, data and AI stacks before costs are ever incurred.

Integration takes less than a day, giving enterprises immediate visibility and rapid savings. FinOpsly also connects natively with systems like JIRA and ServiceNow, feeding optimization actions directly into engineering workflows. Its SOC 2 and ISO 27001 certifications, along with an architecture that avoids ingesting sensitive data, ensure strong security and governance.

Customer results highlight its effectiveness. A global fintech struggling with rising cloud and data platform costs used FinOpsly to identify idle resources, right-size machines, and optimize commitments—saving over $7M on AWS and $10M on Azure in a year, with 15–20% savings in the first 90 days. Other enterprises report similar double-digit savings soon after deployment.

These outcomes reflect more than immediate savings. They show how FinOpsly’s model scales with enterprise environments and supports the company’s plan to expand from cost optimization into broader cloud and AI operations.

As the AI era accelerates, FinOpsly gives enterprises the foundation to innovate boldly while staying cost-aware, accountable and firmly in command of their cloud and AI operations.