CortexIQ builds your digital workforce: growth, service, lending, and compliance, handled by digital employees instead of dashboards. Raw member PII is stripped before anything reaches our infrastructure — only masked, de-identified data ever leaves your systems.
One shared reasoning engine powers every digital employee on your team. Solid nodes are live with measured accuracy today, dashed nodes are live and running but not yet formally accuracy-tuned.
Each digital employee watches for one specific pattern and hands your team a ready-to-act recommendation. None of them execute a transaction on their own.
Flags outbound transfers to competing institutions before deposit flight shows up in monthly reporting.
Spots competitor loan payments in transaction history and surfaces a refinance opportunity your team can act on.
Finds external card and loan payments your institution has no visibility into, and prompts the customer to connect the account.
Finds customers with income but no treasury or savings product, so you can put their idle cash to work.
Detects competitor card spend and recommends a balance-transfer or rewards-migration play.
Flags overdraft and NSF fee events on high-value relationships for fast, consistent, human-approved service recovery.
Turns spending behavior into educational nudges, so engagement doesn't stop at a one-off email campaign.
Demo-grade, LLM-assisted pattern for flagging missing disclosures in outbound loan communications and routing them to Legal — not a certified compliance system.
Runs KYC, risk, and underwriting sub-checks in parallel to compress loan decision time into an audit-ready package.
Watches subscription and recurring-charge drift to surface real, immediate savings moments for members.
We start with your transaction data. From there, your digital employees grow into your accounts, your documents, and your customer conversations too.
Your Plaid and core banking feeds, read for growth, retention, and service signals. The foundation everything else builds on.
Tenure, product depth, and balance trends, so you catch attrition and cross-sell opportunities before a single transaction proves it.
Your loan applications, disclosures, pay stubs, and statements, extracted and reviewed for underwriting and compliance, not just transactions.
Your call transcripts, chat logs, and support tickets, read for service-quality and churn signals your team can't catch manually at scale.
Built to be reliable in your production environment, not just impressive in a demo.
Scrub locally with our free offline tool so raw PII never leaves your network at all — or send data as-is and let our server-side masking handle it. Either way, names, exact amounts, and account identifiers are always stripped before anything reaches an AI model, no exceptions.
One consistent, testable process scores each pattern with a confidence level. No ad-hoc keyword matching.
Only signals above a measured confidence threshold become a recommendation. Ambiguous evidence gets dropped, never guessed at.
Every recommendation is reviewed by your team before it reaches a customer. No autonomous fee waivers, no autonomous approvals.
The practices that make this safe for your institution, built into the code, not just written in a policy.
Every recommendation is reviewed by your team before it reaches a customer. No autonomous fee waivers, approvals, or transactions in this phase.
Every signal carries a confidence score. Anything below a measured threshold is discarded automatically, not surfaced as a guess.
If a model is unreachable or returns a bad output, the system falls back to "no signal detected." It never fabricates a result to fill the gap.
Every recommendation logs its rationale, confidence, and the model that produced it. That's a real trail for your compliance team, not a black box.
Accuracy is evaluated against a labeled test set on your own infrastructure. You get the actual number, not a marketing estimate.
Transient model failures are retried automatically; every agent is covered by an automated regression test before anything ships.
We'd rather show you a real, measured number than promise one. Every new digital employee earns its own measured number before we call it done.
Independently measured against a labeled test set, running entirely on local open-source models. Not a marketing estimate.
Names, exact amounts, and account identifiers are masked before any AI reasoning step. Enforced in code, not policy.
Every recommendation is surfaced for review. No autonomous fee waivers or lending decisions in this phase.
We're looking for one or two forward-thinking financial institutions to help shape the roadmap in exchange for early, discounted access and direct influence over what we build next.
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