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    USE CASES

    The Problem

    Financial Analysis: Governed Access, Automatically

    The Situation

    Finance teams increasingly turn to AI agents to analyze revenue, margins, and operational performance. Left ungoverned, those agents can reach across the ERP, CRM, and operational systems with whatever access their credentials happen to allow, well beyond what the specific question actually requires.

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    What this looks like in practice

    The CFO asks an approved AI agent why margins declined last quarter.

    Purpose: Financial analysis

    Owner: CFO

    Approved workflow: Management reporting and forecasting

    Permitted: Revenue, expenses, inventory, sales, and operational data

    Restricted: Employee-level compensation and unrelated personal information

    The agent combines governed data across the ERP, CRM, and operational systems and produces the analysis. The request fits the agent's approved purpose and authority, so the work proceeds without human intervention.

    “We want AI to answer financial questions quickly. We don't want to find out later that it saw more than it needed to.”

    Customer Support: Access Constrained to the Business Purpose 

    The Situation

    A support agent investigating one customer's issue doesn't need, and shouldn't have, open access to the rest of the customer database. But many AI integrations are granted broad, all-or-nothing access for convenience, because scoping it case by case is harder to build than it sounds.

    What this looks like in practice

    A support agent needs customer information to investigate a service issue.

    Purpose: Customer support

    Owner: VP, Customer Experience

    Approved workflow: Resolve active customer cases

    Permitted: Customer profile, products, service history, and relevant transactions

    Restricted: Other customers' records and unrelated sensitive information

    The agent receives the information necessary for the active case without gaining broad access to the customer database. It gets what it needs to do its job, not everything its underlying credentials might technically allow.

    “We want AI to resolve cases quickly. We don't want it holding more customer data than the case in front of it requires.”

     

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    Production Troubleshooting: Governed Human Escalation 

    The Situation

    Diagnosing a customer-impacting incident sometimes genuinely requires looking at production data, not just logs and telemetry. Handled poorly, that either means the agent is blocked from doing its job, or it's handed standing access to sensitive data it only needed once.

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    What this looks like in practice

    An engineering agent determines that production data is needed to diagnose a customer-impacting incident.

    Purpose: Application troubleshooting

    Owner: VP, Engineering

    Approved workflow: Diagnose production incidents

    Permitted: Telemetry, logs, metadata, and development data, by default

    Restricted: Customer production data, which requires elevated authorization

    Instead of simply failing, or accessing the data because it found credentials that technically allowed it, the agent requests approval from the accountable human. The human approves access to the affected dataset for the specific incident, for a limited period.

    “We want the agent to be useful during an incident. We don't want it holding access to customer production data after the incident is over.”

     

    The All-Purpose Assistant: Access Without a Reason

    The Situation

    An employee asks the company's AI assistant, built into everyday chat, a question that happens to touch more than one system at once. Unlike a person, the assistant doesn't belong to a department or a project. It was provisioned once, centrally, for everyone to use for everything, so no single request carries a business reason Spitfyre can check.

    What this looks like in Practice

    The CFO asks an approved AI agent why 

    An employee asks the company's AI assistant a routine question, and the assistant tries to answer it the same way it would answer anything else.

    Purpose: None declared. The assistant is built to answer any question, so no purpose attaches to this one.

    Owner: No accountable business owner. It was provisioned once, for everyone, not for a specific team or outcome.

    Approved workflow: None. General use isn't an approved workflow.

    Permitted: Nothing beyond what the request can justify.

    Restricted: Everything, until the request states a purpose, an owner, or an approved workflow it belongs to.

    Without a declared purpose, the assistant would otherwise answer a question about the vacation policy the same way it answers a question about a colleague's pay, because nothing about either request carries a reason to check. Spitfyre requires a purpose before it will resolve the request, not after something goes wrong.

    “An assistant that can answer anything, for anyone, isn't a shortcut. It's the access problem we already had, with a friendlier interface.”

     

    Your data. Your terms. Always.

    Build an AI-ready data foundation without surrendering control.

    See how Spitfyre combines managed operations with genuine portability and customer ownership.

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