Private enterprise AI development
Flatlogic scopes and builds AI environments connected to company data, systems, and tools. The first decisions are whose data is accessible, where it goes, and which actions need approval.
What is the total on bill B-104?
Answer with source
PLN 960.00
B-104.pdf page 1 Total due
Flatlogic products and services are used all over the world, including the following notable companies
One request. Three checkpoints.
Illustrative workflow: an Acme Bakery finance reviewer checks bill B-104. The company, bill, and values are fictional.
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Check the user's access
Request: “What is the total on B-104?”
The source permits the finance reviewer to read this bill. A user from another team receives no bill content.
Only permitted data reaches the model.
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Show the answer and source
Answer: “PLN 960.00. B-104.pdf, page 1.”
The reviewer can open the cited page. If the total is unreadable, the answer identifies the missing information.
The amount can be checked against the bill.
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Approve any business change
Next request: “Update the accounting record.”
The reviewer sees the exact proposed change. A separate permission allows the write after approval. The decision and outcome are recorded.
Until approval, the record stays unchanged.
This is a custom development engagement. AI discovery defines the workflow, deployment boundaries, and controls to verify.
From the first document to a working pilot
An example delivery sequence for bill review. Dates depend on source access, deployment requirements, and the agreed scope.
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Map one task and its data
For bill review, identify the finance users, PDF store, accounting system, and permitted model. Output: a data-flow diagram covering source access, retention, logs, backups, and operating owners.
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Build a pilot that can only read
Connect the source and show answers beside their evidence. Ready to advance: an authorized reviewer can inspect B-104; another team cannot retrieve its text, cached answer, or PDF.
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Add a reviewed action
Show the proposed accounting change before a reviewer approves it. Ready to advance: rejection leaves the record untouched, and retrying an approved request does not create a duplicate.
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Test access changes and hand over
Revoke a test user and confirm access stops. Rehearse recovery from a failed connector. Output: the test results, usage and cost records, support owner, and recovery instructions.
Does private AI have to run on-premises?
The data requirement determines the deployment. These are options to assess during scoping, rather than included hosting plans.
| Option | Boundary to confirm | Operating work |
|---|---|---|
| Controlled cloud | Tenant, region, network access, and any external model calls. | Cloud administration, identity, backups, monitoring, and provider charges. |
| Hybrid | Which records stay inside and which context crosses to a model or hosted service. | Both environments, connectivity, credentials, and failure handling. |
| On-premises or local | Whether models, tools, telemetry, and updates can operate within the required boundary. | Hardware capacity, model serving, patching, backups, and support access. |
Before implementation, the responsibility plan names who owns infrastructure, source permissions, business approval, and ongoing support. A customer-hosted application can still send data to an external model unless its data flow excludes that path.
AI integration covers system connections. AI transformation covers rollout into the team's daily work.
Define one private AI workflow
A starting brief identifies the task, users, source systems, required data boundary, and operating owner.