We believe AI costs shouldn't be a black box.
COGScontrol was built by engineers and finance leaders who were asking what AI spend actually buys — two years before it made the front page.
Empowering AI-first companies to scale confidently.
When AI becomes central to your product, costs can spiral quickly. A single runaway prompt, an inefficient model choice, or a sudden spike in usage can blow your budget before you even realize it's happening. In 2026 the rest of the market caught up: Uber's annual AI budget gone by April, and a CEO unsure whether a $40,000-a-month engineer was a problem or a pioneer. The question stopped being what does AI cost and became what is it worth — and almost nobody could answer.
We built COGScontrol because we lived this problem. Traditional cloud cost tools weren't designed for the unique challenges of AI workloads — the multiple providers, the per-token pricing, the need to allocate costs by feature or team. When Uber's COO said the link between tokens spent and value shipped "is not there yet" (Fortune), he named the gap we started building for in 2024.
Justin Moore · Founder & CEO
We built spreadsheets, wrote scripts, and manually reconciled bills across providers. When we realized every AI-first company faces this same problem, we knew there had to be a better way.— Justin Moore · Founder & CEO
Our story
Why we built COGScontrol.
The problem
As AI-powered products grew in popularity, engineering teams found themselves with a new challenge: understanding what AI spending actually returns. Unlike traditional infrastructure costs, AI spending is distributed across multiple providers, priced by usage metrics like tokens and API calls, and often difficult to attribute to specific products or teams.
Finance teams were asking questions that engineering couldn't answer: "What did it cost to serve our enterprise customers last month?" "Which feature is driving our OpenAI bill?" "Are we on track to hit our AI budget?" By 2026 the FinOps Foundation was hearing what its director called "existential crises" as the conversation shifted from "go fast" to "what is this worth?" (TechCrunch)
The insight
We realized that AI value measurement needed a purpose-built solution. Traditional cloud cost tools focus on infrastructure — VMs, storage, network. But AI costs are fundamentally different: they're driven by API calls to external providers, measured in tokens and requests, and need to be classified across multiple business dimensions.
We needed a tool that could ingest data from OpenAI, Anthropic, AWS Bedrock, and cloud providers — all in one place. A tool that could automatically classify costs and let you set budgets on the dimensions that matter to your business.
The solution
COGScontrol was born from this need. We built a platform that gives AI-first companies a measured answer to what their AI spending returns: costs classified and attributed automatically, measured against business metrics, and reconciled to the P&L.
Today, teams use COGScontrol to measure the ROI of their AI initiatives and answer the questions that matter: "What's the cost-per-query for our enterprise tier?" "Which AI feature earns its tokens?" "Is our AI gross margin improving as we scale?"
Our values
What drives us.
Transparency
We believe in clear, honest communication — in our pricing, our product, and our relationships. No hidden fees, no surprise charges, no black boxes.
Excellence
We sweat the details. From pixel-perfect dashboards to reliable daily data ingestion, we build products we're proud to put our name on.
Customer focus
Our customers' success is our success. We listen deeply, respond quickly, and build what matters most to the teams who trust us with their data.
The instrument panel
Built for the resolution finance expects.
Ready to measure the value of your AI investment?
Ready to manage unit economics continuously — instead of scrambling at month-end?