Stop Paying the Hidden Shadow AI Cost

Unsanctioned AI tools create compliance exposure and unpredictable API spend. Jinba replaces that chaos with governed, deterministic workflows that cost a fraction of stochastic LLM agents.

Book a Demo

Give our teams a sanctioned route so they stop reaching for unapproved AI tools. When someone submits a task, check it against our approved workflows and data classification rules. If a governed workflow covers the request, run it with rule-based logic and selective AI calls; if nothing covers it, flag the gap to a compliance officer for review. Alert the CFO and Head of AI when execution cost breaches our monthly AI spend threshold and wait for their approval before continuing, then record the execution details, cost, user, workflow version, and outcome for the audit trail.

Building workflow...

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A Governed Alternative to Shadow AI That Cuts Costs

Jinba Flow gives regulated enterprises a sanctioned, auditable AI workflow platform so teams stop reaching for unsanctioned cloud AI tools. With deterministic execution at its core, Jinba is architecturally cheaper to run at scale than stochastic LLM agents, directly answering CFO pressure on enterprise AI spend.

Describe any compliance or document workflow in plain language, generate a workflow draft instantly, and refine it in a visual editor so teams always use approved, governed automations instead of shadow tools
Configure routing rules, cost thresholds, and exception paths so every workflow execution follows defined business logic rather than unpredictable AI inference on every call
Validate inputs and enrich data from internal systems such as core banking platforms, document repositories, and compliance databases before any action is taken
Every execution is logged with a full audit trail, timestamps, and role-based access controls so compliance officers can evidence exactly who ran what and when

How Jinba Replaces Shadow AI With Governed Workflows

Send weekly metrics to Slack every Monday at 9am

1

Build in Jinba Flow

Solution engineers and operations teams use Jinba Flow to build compliant workflow automations via chat-to-flow generation or a visual editor, setting routing rules, validation logic, and access permissions in one place.

test_runner.log

Running workflow test...

✓ Input validation 12ms

✓ Fetch from Sheets API 847ms

✓ Process 24 rows 156ms

✓ Send to #sales 203ms

PASS All steps completed 1.22s

Output preview:

"sent": true, "channel": "#sales"

2

Deploy securely (API / batch / MCP)

Workflows are published as APIs, batch processes, or MCP servers and shared across the entire organisation with RBAC, SSO, and Active Directory integration, removing the need for individuals to reach for unsanctioned cloud AI tools.

3

Run in Jinba App (guardrailed UI)

Business users in Jinba App execute approved workflows through a conversational interface with auto-generated forms, keeping execution deterministic, auditable, and fully within the enterprise governance boundary.

Enterprise Ready

Control, security, and support for large organizations.

On-Prem

Jinba

Private

On-premises or private cloud hosting

Run Jinba in your own environment with full data control.

Team Permissions

128 Active

Sarah Chen Engineering Lead

Workflows

Michael Ross Product Manager

Analytics

Guest User External Auditor

Admin Access

SSO Enforced

Updated 2m ago

Advanced access control

Role-based permissions and SSO integration.

audit_stream.log

1

[200] 09:14:22 GET /api/v1/health_check

2

[INFO] 09:14:23 Worker node_04 connected

3

[AUTH] 09:15:01 User admin@corp verified

4

[AUDIT] 09:15:02 Role assignment update

5

// Syncing to edge...

6

[200] 09:15:08 Config updated

Audit logging

Complete compliance and security oversight tracking.

Marketing

RESTRICTED

HR

ALLOWED

Screening

Automation

Organization management

Spaces, roles, and approvals for your team.

OpenAI

Gmail

Slack

HubSpot

Salesforce

Notion

Linear

GitHub

Teams

Dropbox

OpenAI

Gmail

Slack

HubSpot

Salesforce

Notion

Linear

GitHub

Teams

Dropbox

Pre-built & custom integrations

100+ pre-built integrations plus custom connectors for your internal systems.

Alice 10:42 AM

We need a connector for our internal CRM. Is this possible?

James 10:43 AM

Sure! Can you share the API spec?

crm_api_spec.pdf

Got it. I'll have the connector ready by tomorrow.

James Next day

Connector is live!

Thank you!

Dedicated Engineer Support

Work side-by-side with our engineers to remove blockers and accelerate your workflow development.

AWS Bedrock Claude 3.5 Sonnet

Azure OpenAI GPT-4 Turbo

Meta Llama 3 Self-hosted 70B

Private model hosting

Use Bedrock, Azure AI, or your own models securely.

On-Prem

Jinba

Private

On-premises or private cloud hosting

Run Jinba in your own environment with full data control.

Team Permissions

128 Active

Sarah Chen Engineering Lead

Workflows

Michael Ross Product Manager

Analytics

Guest User External Auditor

Admin Access

SSO Enforced

Updated 2m ago

Advanced access control

Role-based permissions and SSO integration.

audit_stream.log

1

[200] 09:14:22 GET /api/v1/health_check

2

[INFO] 09:14:23 Worker node_04 connected

3

[AUTH] 09:15:01 User admin@corp verified

4

[AUDIT] 09:15:02 Role assignment update

5

// Syncing to edge...

6

[200] 09:15:08 Config updated

Audit logging

Complete compliance and security oversight tracking.

Marketing

RESTRICTED

HR

ALLOWED

Screening

Automation

Organization management

Spaces, roles, and approvals for your team.

OpenAI

Gmail

Slack

HubSpot

Salesforce

Notion

Linear

GitHub

Teams

Dropbox

OpenAI

Gmail

Slack

HubSpot

Salesforce

Notion

Linear

GitHub

Teams

Dropbox

Pre-built & custom integrations

100+ pre-built integrations plus custom connectors for your internal systems.

Alice 10:42 AM

We need a connector for our internal CRM. Is this possible?

James 10:43 AM

Sure! Can you share the API spec?

crm_api_spec.pdf

Got it. I'll have the connector ready by tomorrow.

James Next day

Connector is live!

Thank you!

Dedicated Engineer Support

Work side-by-side with our engineers to remove blockers and accelerate your workflow development.

AWS Bedrock Claude 3.5 Sonnet

Azure OpenAI GPT-4 Turbo

Meta Llama 3 Self-hosted 70B

Private model hosting

Use Bedrock, Azure AI, or your own models securely.

Get Your Shadow AI Cost Assessment

If your teams are running unsanctioned AI tools and your CFO is asking questions about AI spend, Jinba can help you audit your exposure and replace it with a governed, cost-efficient alternative.

Book a Demo

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.

What is shadow AI cost in a regulated enterprise?

Shadow AI cost refers to the financial and compliance exposure created when employees use unsanctioned AI tools. Cloud-based LLMs, personal ChatGPT accounts, and unvetted API integrations used without IT or compliance oversight all contribute. For banks and insurers this includes unpredictable API spend, data leakage risk, and the operational overhead of investigating and remediating unsanctioned tool usage.

Why are stochastic LLM agents so expensive to run at scale?

Stochastic AI agents call an LLM on every step of every workflow execution, burning tokens continuously. Jinba's deterministic architecture runs 80% of workflow logic as rule-based steps, using AI only where genuinely needed. This structural difference, not prompt optimisation, creates a significant cost advantage when enterprises move from pilots to production at scale.

How does Jinba reduce enterprise AI API spend?

Jinba Flow builds 80% rule-based, deterministic workflows so that routine compliance checks, document routing, and validation steps do not require an LLM call. AI is invoked selectively, not on every execution. This architectural approach reduces running costs compared to stochastic AI agent equivalents and gives CFOs a predictable, governable AI spend profile.

Can Jinba run on-premise without sending data to cloud AI providers?

Yes. Jinba deploys on-premise or in a private cloud and supports private model hosting via AWS Bedrock, Azure AI, or self-hosted models. Data never leaves the enterprise environment, which is critical for banks and insurers that cannot put customer or compliance documents into public cloud AI services.

How does Jinba prevent employees from using shadow AI tools?

By giving teams a sanctioned, easy-to-use alternative. Jinba Flow lets technical and semi-technical staff build approved workflows quickly via chat-to-flow generation. Jinba App gives non-technical users a governed conversational interface to run those workflows. When a compliant tool is faster and easier than a shadow tool, adoption of unsanctioned alternatives drops.

Is Jinba suitable for compliance-heavy workflows like KYC or loan underwriting?

Yes. Jinba is built for regulated industries including banking and insurance. It supports KYC document processing, loan underwriting automation, compliance checks, and contract review workflows with full audit logging, RBAC, version control, and on-premise deployment. These are the controls financial regulators expect.

How quickly can we replace shadow AI workflows with Jinba?

Jinba's chat-to-flow generation means technical teams can build and deploy governed workflow automations in days rather than the months typical of traditional RPA or consultant-led projects. Jinba AI Consulting also offers a free AI strategy assessment to help organisations identify shadow AI exposure and prioritise which workflows to govern first.

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