The $3 Trillion Problem Hiding in Corporate Contracts, and the AI Built to Find It
Terzo says Fortune 500 companies have recovered hundreds of millions of dollars that leaked out of deals they had already won.
Across the global B2B economy, trillions of dollars in value are exposed to leakage between what companies negotiate and what they ultimately pay, consume and recover. It isn’t stolen, and it isn’t lost in a market crash. It leaks out quietly, through invoices that creep above contracted rates, renewals that fire on autopilot, rebates nobody claims, and warranties nobody enforces.
Brandon Card saw the problem up close long before he tried to solve it. In 2018, he was working at Microsoft, managing nine-figure enterprise deals, when a global automaker asked him to summarize its Microsoft agreements. The answer was a 95-slide PowerPoint, one screenshot of a contract for every country.
“I’m in meetings over here talking about sending Teslas to Mars,” Card recalled. “And then I’m over here building a PowerPoint with ninety-five slides for contract data. This just doesn’t make sense.”
Card had spent a decade at Oracle, IBM and Microsoft watching the same pattern repeat. The largest companies on earth negotiated hard for pricing, volume tiers and service guarantees, then filed the signed contract in a repository and moved on. Reality drifted. The savings walked back out the door. In 2020 he left to found Terzo, an AI platform built on a simple idea: contracts are not legal paperwork. They are financial assets, and almost nobody manages them that way.
The gap between what was agreed and what was paid
Terzo converts contracts, amendments, purchase orders, invoices and supplier data into a structured financial intelligence layer, then continuously compares what the enterprise agreed to with what it actually buys, uses and pays for.
When a master services agreement caps annual price increases at three percent and an invoice arrives at 8.2 percent higher than last year, the platform flags it, attaches the evidence, calculates the dollar value and routes it for recovery.
What began as AI contract intelligence has evolved into a broader financial intelligence platform. Terzo structures the commercial data buried across contracts, invoices, purchase orders and enterprise systems, connects those relationships in a financial graph, and deploys AI agents against that data to continuously identify savings, renewal opportunities, pricing anomalies and financial risk.
That kind of discrepancy is easy to miss when a large enterprise makes hundreds of thousands of financial decisions a year. Card describes it as a scale problem, not a people problem. Auditors and consultants can sample a sliver of the transactions. Software can review all of them.
Why the Model Isn’t the Moat
The explosion of large language models has made it relatively easy to summarize a contract. Card argues that isn’t the hard problem. The hard problem is creating trustworthy, structured financial data from millions of messy enterprise documents and connecting that data to what actually happened in the business.
Gartner predicts that through 2026, organizations will abandon 60 percent of AI projects unsupported by AI-ready data.
Terzo’s answer is a human in the loop model. Its AI extracts every clause, obligation and SKU, and human reviewers validate the output to a contractual accuracy guarantee above 99 percent. The company has processed more than $500 billion in enterprise agreements and over two million contracts.
“The only way to solve this is with AI,” Card said. “That was the moment I knew it was worth going all in.”
Results at Fortune 500 scale
The numbers Terzo cites are large. A Fortune 500 company reports $300 million saved across procurement, and one of its senior procurement executives has called Terzo “the system of truth for tracking $8B of spend in my org.” Another saved $25 million in IT spend in its first year. A third has verified $250 million in savings across its supply chain.
The pitch to CFOs and chief procurement officers is that none of this requires ripping out existing systems. Terzo does not replace the ERP or the contract repository. It connects them. Initial deployment takes about a month, the client commitment is roughly an hour a week, and first findings typically land within 90 days.
Terzo works with Fortune 500 companies across 14 industries, from technology and retail to aviation, consumer goods and health insurance. The company has raised $60 million and was named by Business Insider as one of the startups most likely to become tech’s next unicorn.
For Card, the mission has not changed since the 95-slide PowerPoint. What has changed is the scale of the opportunity. As enterprises rush to deploy AI agents, Terzo is betting that the winners will not be the companies with the most chatbots, but the ones with the cleanest financial data and the clearest connection between AI and measurable economic outcomes.
“Every enterprise has money it can’t see,” Card said. “Our job is to find it.”
