6 What are you giving up?
A disconnected laptop answers a question using a model stored on its disk. That is useful evidence: this particular request could complete without a live network connection. It is not evidence that the application never logs prompts, that backups are local, or that no data will be transmitted when connectivity returns.
Deployment decisions improve when the claim is that specific. “Local is private” and “enterprise is compliant” are both too broad. The task is to identify what each arrangement controls, what it costs, and what remains unverified.
6.1 Three arrangements to compare
A managed service operates the model for you. Depending on the product and contract, you may gain rapid setup, supported integrations, or access to particular models. You depend on the service’s availability, terms, limits, and data-handling arrangements.
A self-managed hosted service runs on infrastructure you administer or contract for. You may choose a region and model, but you also inherit operational work. Hosting, storage, telemetry, support, backups, and connected tools can have different locations and access rules.
A local installation can process a request entirely on the device. That can be valuable for offline work or a restricted data flow. Hardware capacity, updates, access control, lost devices, electricity, and support are still costs. A local engine connected to a remote tool is no longer an entirely local workflow.
None of these labels establishes which candidate is most capable on your task. Compare the actual candidates against the same proof brief. An open-weight model permits access to weights under its licence; it does not necessarily provide training data, unlimited redistribution rights, or freedom from software dependencies.
6.2 Count the whole cost
Subscription and usage-based billing are common, sometimes within the same product. Do not assume a subscription is unlimited or that every enterprise agreement bills by token. Record the actual unit, included allowance, overage rule, concurrency limit, and cancellation terms for the offer being assessed.
For a simple invented budget exercise, suppose Candidate A costs 30 currency units per seat-month for ten seats, with the planned use within its allowance. Candidate B costs 0.02 units per completed request. At 10,000 requests, A costs 300 and B costs 200; at 20,000, B costs 400. These figures are arithmetic inputs, not market prices. They exclude setup, review, retries, storage, and tax.
A local option may have no provider charge per request while still consuming electricity and staff time. A recurring job that needs five minutes of review can cost more in attention than in inference. An agent that retries repeatedly changes the effective cost per completed job. Budget for successful, reviewed outcomes, not merely the cheapest advertised token.
Lower unit cost can encourage greater use; it does not determine total demand. Treat usage growth as a scenario to test. The final chapter returns to this distinction when considering workforce and service effects.
6.3 Read commitments at the product level
A familiar brand name tells you little about the permissions attached to a particular account. For each candidate, gather the current agreement and configuration:
- What may be submitted, and for which purpose?
- Who can access prompts, documents, outputs, and logs?
- Is content eligible for training, and under which controls?
- Where is each part processed, retained, and backed up?
- Which connected services or subprocessors receive it?
- What deletion, export, audit, and incident processes are available?
A no-training commitment answers one question, not all six. Certifications can contribute evidence about a defined scope; they do not approve your use case automatically. Have the relevant privacy, security, procurement, and legal owners assess the proposal before sending real records.
For Australian organisations, OAIC’s AI guidance recommends product due diligence and a cautious approach to personal information. It does not make an “enterprise” label a blanket approval. OAIC, guidance on commercially available AI products
6.4 Residency is not the whole jurisdiction question
Residency concerns where data is stored or processed. Jurisdiction concerns applicable legal authority; ownership, provider obligations, contracts, and the parties involved can matter as well as server location.
The US CLOUD Act clarifies obligations concerning data within a provider’s possession, custody, or control, including data held abroad, under applicable legal process. It also provides a framework for certain international agreements. It is not a rule that every US company exposes every record to any request. A Sydney address alone is not a complete legal analysis. Consult the official materials and qualified advice for the actual arrangement. US Department of Justice: CLOUD Act resources
Local processing may remove a particular transfer from the workflow. It does not remove privacy obligations, authorised-access risks, or every possible jurisdictional issue. Do not ask an AI to turn an architecture sketch into a legal verdict.
6.5 Tessera’s decision, with the unknowns left visible
Suppose Tessera wants draft summaries of support tickets. Its internal proposal lists three candidates but has not supplied complete contracts or a benchmark. The honest table looks like this:
| Candidate | Possible advantage | Evidence still required |
|---|---|---|
| Managed service | Less operational setup | Approved data flow, contractual scope, access/retention controls, task evaluation |
| Self-managed regional host | Choice of region and deployment configuration | Backup/support locations, maintenance owner, security controls, realistic cost |
| Local installation | Request can run offline | Hardware suitability, logs/connectors/backups, access controls, measured quality |
The table does not name a winner. That is a strength when the evidence is missing. The team can test all three with synthetic material while withholding real tickets until the relevant approvals exist.
Illustrative conversation: an assistant recommends the managed service because it expects better writing. The practitioner asks for the test results and the approved data flow. Neither exists. The corrected recommendation is to run a bounded comparison with invented inputs and obtain the missing approvals. The practitioner has not proved the service unsuitable; they have shown that the proposed decision was premature.
6.6 Core: write a procurement memo
Time: 30 minutes. Inputs: the three candidates above, the invented budget figures, and this constraint: no real customer records may leave the approved environment without review.
- Calculate the two request-volume scenarios.
- List which costs are omitted and could change the comparison.
- Mark the evidence gaps that prevent a real-data pilot.
- Recommend a next step that is possible now, using Appendix G’s synthetic sources.
- Name the role that can approve the subsequent data use.
Artefact: a one-page comparison in the dossier. Success: show both cost calculations, make no unsupported capability ranking, and distinguish permission to experiment with invented data from permission to process customer records.
Optional local experiment: use the current setup documentation in Appendix F to run a suitable model. Record the exact version, hardware, configuration, and whether a new synthetic request succeeds while disconnected. Check logs and connected services separately. Do not expose a local server to a network merely to complete the exercise. If setup fails, record the result; the paper decision remains complete.
6.7 Keep an exit route
Portability starts with the records you control: test cases, source versions, data dictionaries, prompts, evaluation scripts, and decisions. Keep them in ordinary formats where feasible. Replacing a model may still require adapting tool calls, context handling, or output validation; open weights do not make all implementations interchangeable.
Before choosing an option, describe how you would leave it. Can you export the necessary records? Re-run the baseline? Revoke access? Verify deletion under the applicable agreement? Who would own the migration?
This closes the Foundation act. You have a task, an affected population, a data boundary, and deployment constraints. The next chapter uses them to design a source-grounded interaction rather than letting a convenient interface define the job.