Real AI.For real banking.
Launch financial products, automate decisions and serve customers with AI that runs inside the operating system.
Book a demoThe problem
Legacy systems are keeping banks from using AI
Most AI gets added on top of a patchwork of legacy systems, so it can’t reach the accounts and customers it’s meant to serve.
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Fragmented data
Accounts, products and customer data sit in systems that were never built to talk to each other. AI works on incomplete copies, so it can answer questions but can’t act.
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AI without guardrails
In banking, one wrong action is a compliance breach. Every action needs an owner and an approval.
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Customer data at risk
Regulators expect customer data to stay protected and in-country but most AI tools send it somewhere banks can’t see.
The solution
A modern operating system, with AI built in
Stitch AI runs inside the operating system with direct access to accounts, decisions and customers, under the same rules as the team.
New loan product
Product details
Deferrals
Rescheduling
Capitalize overdue repaymentsCapitalize overdue feesAllow backdatingMaintain account number
01 Copilot
One copilot to query, configure and launch
Ask for data, set up a new product, change a workflow or update pricing in plain language. The copilot pulls the answer or makes the change, and every change waits for approval.
Describe the product and I’ll fill all 42 settings
Personal loan for direct-deposit customers. $2,000 to $50,000 over 12 to 60 months, priced 8.9% to 14.9% APR by risk band, 1% origination fee capped at $500, paid into their checking account.
Attach
02 Prebuilt agents
Put an agent to work in one step
Ready-made agents for onboarding, fraud checks, collections and customer service. Add one to any workflow with a single request.
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03 Custom agents
Build banking-grade agents on one governed harness
Give an agent a job, choose which Stitch services and systems it can use, test it on live data, then publish. Permissions, approvals, guardrails and audit come built in, so every agent is ready for a regulated bank.
Custom agent · built in Agent Studio
Built Tested PublishedDescription
Review accounts 31–60 days past due and prepare a masked follow-up list for the collections team.
Governed harness
| Rules | What matched | Decision |
|---|---|---|
| No bulk export of personal data | SSNs, Phone No, Account No | Blocked |
| Customer data stays inside Stitch | Email to Gmail | Blocked |
| Masked list in chat | 31–60 day bucket, fields masked | Allowed |
All three act within the limits the institution sets. Above them, they ask.
Why Stitch AI
AI built for financial services
General-purpose AI tools weren’t designed for banking. With Stitch AI, every action stays inside the rules, environment and ledger a financial institution already runs on.
Control
Governed by design
Every agent has its own identity, scoped permissions, hard limits, maker-checker and a full audit trail. Sensitive data is masked before a model ever sees it. The operating system enforces it all, so nothing runs outside it.
Choice
Any environment, any model, full choice
Run it in-country or in a private cloud, on open, closed or custom models. Swap models without rebuilding anything.
Impact
Built in, not bolted on
Agents act on the ledger itself, through the same services the products already run on. No copies, no connectors, no AI that only works in a demo.
Anyone can be a hero
Starring Patrick J. Adams. The film behind the launch of Stitch AI.
Request a demo
See Stitch AI on real banking products
Book a demo to see the copilot and an agent at work on real banking products.
Frequently asked questions
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AI that runs inside a modern operating system. It includes a copilot that sets up products and workflows, ready-made agents for everyday work, and tools to build custom agents.
Any bank or lender with a modern operating system, or one in the middle of modernising it.
Any model: open, closed or a custom one. Models can be switched later without rebuilding anything.
Yes. Stitch AI can run in-country or in a private cloud, and personal data is masked before any model sees it.
Agents only do what the signed-in person is allowed to do. Every change needs a second approval, and every action is logged.
AI needs live data and clear controls to act safely. A modern operating system provides both, so agents work directly on real accounts.
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