The AI infrastructure layer for mid-market investors, and the operating companies behind every deal.
Three intelligence priors. 1,757 reasoning chains. One framework. Built for the people who decide which companies to buy, hold, and sell. And the founders who need to be ready when they call.
Three audiences. One library.
CevantAI ships the same 1,757-chain reasoning library to three distinct buyers. Self-select the surface that matches you. We'll send the right proof design to your inbox in one business day.
Run it on a target.
PE, private credit, search funds, sell-side advisors. Adversarial DD, screening memos, portfolio diagnostic, monitoring. Full audit trail.
See investor bundles →Run it on yourself.
Founders raising. Scale-ups preparing for exit. PortCos prepping for sell-side. Investor-grade readiness, recalibrated to your stage.
See readiness bundles →Run it on your workflows.
RevOps, legal, claims, procurement. Sprint → Build → Subscription, delivered FDE-style inside your VPC.
See Operate model →Deployed inside your infrastructure. Your data never leaves your environment.
As frontier models improve, your capability improves. No rebuild required.
Built to satisfy audit requirements. Every finding traceable to source.
Adversarial verification, not just synthesis. Built to question everything.
Synthesis tools read documents.
Institutional decisions need interrogation.
Every reasoning chain in our library is classified by intent. The system knows what it is being asked to do before it answers. No competitor we have identified ships adversarial reasoning as a first-class prior.
Interrogate
Counterparty has incentive to mislead. The engine assumes documents are wrong and hunts contradictions across the data room. Primary use: due diligence, credit review, fraud detection.
Reconcile
Multiple sources, one truth. The engine reconciles them into a single picture and flags what does not add up. Primary use: portfolio monitoring, covenant tracking, integration.
Build
Build IC-ready output structured to committee standards, with full audit trail from source to conclusion. Primary use: IC memos, credit committee reports, sell-side packs.
Neither wrong in isolation.
A capital costs schedule showed commissioning completing Q1 Year 3.
A financial model showed revenue starting Year 4. Both documents internally consistent. Both passed standard review. Together, they described a full year of capital exposure with zero revenue.
Q1 Year 3.
Year 4.
COOs and CTOs are asking whether your AI capability can be audited, scaled across the organization, and upgraded as models improve. This is not a future requirement. It is being asked on live mandates now.
"We use ChatGPT"
"We embedded adversarial AI infrastructure that runs 1,757 verification chains across 97 modules against every data room, classified across three intelligence priors, with full audit trails built to IC requirements."
Built for workflows where
the cost of a miss is highest.
We start in institutional finance: due diligence, portfolio monitoring, credit underwriting, compliance review. These workflows demand adversarial verification and institutional-grade auditability. This is our beachhead, not our boundary.
Due Diligence
Adversarial review across 100% of the data room. Cross-document contradiction detection before any investment case is built. Every finding traceable to source.
See the use case →Portfolio Monitoring
Continuous surveillance across your portfolio. Leading-indicator alerts for covenant drift and credit stress before the reporting cycle. Proactive, not reactive.
See the use case →Credit Analysis
Structured credit analysis with full audit trail. Built to your credit committee format. Every conclusion traceable from source to recommendation.
See the use case →KYC Review
Beneficial ownership traced through complex structures across jurisdictions. Inconsistencies surfaced automatically with full compliance audit trail.
See the use case →The only firm doing adversarial AI at institutional scale.
If your current AI capability can't hold up to institutional scrutiny, we should talk.
Start with Proof