Industries / Fintech
AI for financial products, built by fintech engineers.
AI agents and workflows for lending, payments and wealth teams, built by engineers who have shipped fintech and DeFi platforms. Accuracy, auditability and human review are designed in.
Where it fits
Example use cases.
Generic examples of where AI fits in fintech operations, not client results.
Intake
Document intake
Read applications and statements, extract fields, flag what needs a person.
Credit
Underwriting support
Summarise files and surface risks for an analyst, who makes the decision.
Support
Customer support agents
Answer account questions with the right data and hand off sensitive cases.
Reporting
Operational reporting
Reconcile and report with every number traced to its source.
How we build
How we handle risk and review.
In financial services an agent never makes the final call on money or credit. It prepares, checks and escalates.
- → human approval on every decision that moves money or changes credit
- → audit trails for every agent step
- → evaluation sets built from your real cases
- → deployment in your own cloud setup
Deployed where your data lives
Your AI runs inside the cloud you already trust.
We pick the platform around where your data, identity and security controls already are.
For teams on Microsoft identity and Azure data services.
For data in BigQuery and workloads on Google Cloud.
For agents that stay inside your AWS accounts and VPCs.
For a managed agent runtime when it fits your controls.
Proof
Fintech and DeFi we've built.
Client · fintech
Levenue
A revenue-based financing platform we built for a client.
See the project →Our product · AI
TradeMindAI
AI-assisted technical analysis for stocks, crypto and forex. Our own product, live on iOS.
Read the case study →Client · web3
DeFi lending platform
A lending protocol front end and smart-contract integration we built for a client.
See the project →How we engage
Start small. Earn the next step.
Pick the workflow worth automating
Interviews, a data and integration audit, a ranked use-case list and a build plan with running costs.
Prove it on your data
One workflow, connected to real systems, measured against criteria agreed up front.
Ship it properly
Integrations, evaluation, monitoring, security review steps, documentation and handover.
Keep it working
Evaluation runs, model and provider updates, cost control and a monthly report.
Questions
What buyers ask us first.
Where does our data go?
It stays in the cloud setup you already use. We build on Azure AI Foundry, Google Vertex AI, AWS Bedrock or Claude Platform, chosen around where your data, identity and security controls already live.
Will an agent approve loans or payments?
No. Agents prepare and check; a person approves anything that moves money or changes credit.
What does it cost to run?
Every scoping sprint ends with a cost model for both the build and the running costs. Systems we ship come with per-agent cost tracking and hard spending caps.
Book an AI scoping call
Bring one workflow. We'll tell you if an agent should run it.
or write to contact@byteandrise.com · we work under NDA