Give analysts the facts they need
Turn documents, articles and case records into structured information your team can review. Munito AI gives fintech teams open models and document AI on European infrastructure, with zero data retention by default.
Build the workflow around your analysts: extract the facts, connect them to source material and prepare a clear case summary. Keep the final decision with your team.
From documents to a reviewable case
| Workload | Build with Munito AI |
|---|---|
| Document extraction | Convert pages to Markdown and extract the fields your workflow needs |
| Adverse media review | Summarize supplied articles and identify relevant passages for an analyst |
| Case preparation | Assemble supplied records into a structured summary with evidence references |
Use Document AI for extraction and structured outputs for predictable response formats. Choose from EU-hosted open models for each stage of the workflow. Connect your own data sources, review rules and case system through the API.
Keep sensitive work in Europe
Run inference on European infrastructure that Munito AI operates, in your own cloud account, or on-premises. Keep customer content in the EU and choose the deployment that fits your customer's requirements. Your team keeps one API across models and deployment choices.
Munito AI does not train on customer data. Zero data retention is the default; your application chooses when to retain outputs for later use. Keep source references and analyst decisions in your own case record.
Give your customer's security team clear answers
Bring a DPA, a documented data policy and a defined deployment to the review. Our SOC 2 audit and ISO 27001 certification work are in progress. Our engineers can discuss the workload directly with your engineering and security teams.
The security review guide collects the documents for that discussion. For DORA assessments, review service scope, locations, incident responsibilities and exit terms against Article 30.
Prove the workflow on your cases
Start with one task and a fixed evaluation set. Measure extraction accuracy, evidence quality, latency and cost per completed case. Review the results with the analysts who will use the system.
Move to dedicated capacity when your workload needs predictable throughput. Keep the same API as you expand from an initial use case to more of your workflow.
Talk to an engineer about your workload, data requirements and evaluation.