Integrate LlamaCloud with Jinba

Connecting LlamaCloud to Jinba Flow lets regulated enterprises parse, index, and route documents inside governed, on-premise workflows. Automate KYC document intake with full audit logging and deterministic execution.

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  1. Document pack arrives Forms, statements and scanned originals
  2. Parse with LlamaCloud Tables and layout preserved as structured text
  3. Extract the fields Pull what the case actually needs
  4. Confidence gate Anything uncertain goes to a reviewer
  5. Write to the case Structured record plus the source pages

What you can do with LlamaCloud + Jinba

  • Governed Document Parsing at Scale

    Route LlamaCloud document parsing outputs directly into Jinba Flow workflows, ensuring every extraction step is logged, versioned, and executed deterministically — with no data leaving your private environment.

  • On-Premise Deployment for Compliance

    Run LlamaCloud-connected workflows on-premise or in a private cloud, meeting the air-gapped deployment requirements of banks, insurers, and healthcare organizations operating under strict data residency rules.

  • Team-Wide Workflow Sharing and RBAC

    Workflows built with LlamaCloud connectors in Jinba Flow are shared across operations teams with role-based permissions, SSO, and Active Directory integration — not siloed to individual users.

  • Audit Logs for Regulatory Accountability

    Every document processed through a LlamaCloud-connected Jinba workflow generates a full audit trail, giving compliance officers and regulators a verifiable record of every action taken.

How teams use it

KYC Document Intake Automation

Use LlamaCloud parsing within Jinba Flow to extract, classify, and route identity documents through multi-step KYC workflows with deterministic logic, audit logging, and team-controlled permissions.

Contract Review and Compliance Checking

Parse contract documents via LlamaCloud and pass structured outputs into Jinba Flow compliance-check workflows, enabling legal and operations teams to review agreements against policy rules consistently.

Loan Underwriting Document Processing

Automatically ingest and parse loan application documents through LlamaCloud, then route extracted data into Jinba underwriting workflows with version-controlled rules and full auditability for regulatory review.

Regulatory Compliance Workflow Automation

Connect LlamaCloud document indexing to Jinba Flow to build repeatable compliance reporting workflows that execute deterministically, produce audit logs, and can be deployed inside air-gapped enterprise environments.

Patient Document Workflow Processing

Parse healthcare intake and authorization documents with LlamaCloud and route them through Jinba Flow workflows with RBAC controls and audit logging, keeping sensitive patient data within your private deployment.

Works well with

Microsoft SharePointMicrosoft 365

Automate document intake, extraction and routing

AWS Bedrock Knowledge BaseSearch & Data

RAG and document sync inside your own VPC

Microsoft OneDriveMicrosoft 365

Pull files into flows and write results back

OpenAIAI Models

Call OpenAI models from any flow

Anthropic (Claude)AI Models

Invoke Claude models as a workflow step

Frequently Asked Questions

Everything you need to know about Jinba. Can't find the answer you're looking for? Reach out to our support team.

Does the LlamaCloud integration with Jinba support on-premise deployment?

Yes. Jinba Flow supports on-premise and private-cloud deployment, including air-gapped environments. When you build a LlamaCloud-connected workflow in Jinba, the entire execution can run within your private infrastructure. Data processed through LlamaCloud parsing does not need to pass through a public AI model or external service, giving regulated enterprises the data residency control required by banking, insurance, and healthcare compliance frameworks.

Is document data sent to a public AI model when using LlamaCloud with Jinba?

Not by default. Jinba supports private model hosting via AWS Bedrock, Azure AI, or self-hosted models. LlamaCloud-connected workflows in Jinba Flow use deterministic, rule-based execution for the majority of steps, which means LLM calls are invoked only where necessary. You control where model inference runs, ensuring sensitive KYC, contract, or patient documents are not routed to unauthorized external endpoints.

Does Jinba produce audit logs for LlamaCloud document processing workflows?

Yes. Every workflow execution in Jinba Flow generates a full audit log, recording inputs, outputs, and each step taken. For LlamaCloud-connected workflows handling regulated documents such as KYC packages, loan files, or contracts, these logs provide the verifiable record compliance officers and auditors require. Audit logging is built into the platform and cannot be disabled for regulated deployment configurations.

How does Jinba handle team access controls for LlamaCloud-connected workflows?

Jinba is a team platform with role-based access control (RBAC), SSO, and Active Directory integration. Workflows built with LlamaCloud connectors in Jinba Flow are shared across your operations team under defined permissions. Builders create and publish workflows; business users execute them via Jinba App without accessing underlying configuration. This separation ensures only authorized personnel interact with sensitive document automation workflows.

How long does it take to build a LlamaCloud workflow in Jinba?

Jinba Flow supports chat-to-flow generation, where you describe the automation in natural language and Jinba produces a workflow draft. Teams then refine the workflow in a visual flowchart editor and test it with real data before deploying it as an API, batch process, or MCP server. Regulated enterprises commonly go from requirements to a deployable LlamaCloud-connected workflow in days rather than the months typical of consultant-led implementations.

Ready to Govern Your Document Workflows

Talk to our team about connecting LlamaCloud to Jinba Flow for compliant, on-premise document workflow automation.

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