Record the current investigation before the demo
Choose a representative investigation your team understands. Record the sources used and the effort needed to reach a defensible decision. Keep the original evidence so the product answer can be checked.
A historical case can be useful when it can be shared under your data-handling rules. A controlled synthetic case can also work when the expected events and limits are documented. Do not use an invented scenario as a customer success claim.
Give each candidate the same evidence and acceptance criteria. A vendor demonstration is useful introduction material; a controlled comparison tells you more about your environment.
Use a common AI SIEM acceptance plan
| Test | What the product must show | Evidence to keep |
|---|---|---|
| Source and field coverage | Expected records with correct identity and event time. | Original samples and received records. |
| Investigation quality | A reproducible answer with supporting evidence. | Case timeline and source references. |
| Missing-data handling | A clear statement of what cannot be concluded. | The incomplete sample and product answer. |
| Permission boundaries | Access and actions limited to the approved scope. | Role settings and test outcomes. |
| Commercial fit | Usage that can be reconciled to the quoted meter. | Usage report and pricing assumptions. |
Prove the expected events arrived
Match original records to the data in the SIEM. Look for parsing failures and duplicate records as well as missing ones. Confirm account identity and timestamps before judging the AI narrative.
For IBM i, use an authorized test entry from the actual collection method. A cloud-only sample does not prove business-system integration. Use the IBM i source checks to qualify that part of the test.
Check the answer independently
Ask the platform to explain what happened and what action the analyst should consider. Have an analyst compare the answer with the original evidence.
Record the time to a supported decision. Track corrections and the work required to obtain omitted context. A fast initial answer can still require substantial review.
Repeat the case after a relevant mapping or detection change. Keep the test inputs stable enough that the result can be compared.
Remove a source and watch the conclusion
Repeat the investigation with a known source absent or delayed. The product should identify the limitation and avoid inventing the missing part of the story.
Also include benign activity resembling the suspicious case. Check whether the explanation changes when the evidence does. Record both false escalations and missed expected signals.
Test permissions with approved test identities
Use roles representative of the proposed deployment. Verify that another customer or restricted source cannot be read under the test role.
For response, show that an unapproved change is stopped and an approved test action is recorded. Use a harmless test target with a documented recovery method. The governance guide explains the boundaries to test.
Reconcile the pilot with the commercial proposal
Measure usage at the point the proposal bills it. Confirm which collection methods and detection features the selected tier includes. Include AI or automation charges when applicable.
Ask whether the pilot support you received is included in ordinary service. Separate implementation help from ongoing monitoring so the operating model is clear.
Test historical search and case export before accepting retention and exit assumptions. Review the retention requirements alongside the price.
Make the acceptance decision reviewable
Agree on required results before the test begins. Classify each requirement as passed, failed or not tested and attach its evidence. Keep important gaps visible even when the overall demonstration is strong.
Accept a production rollout when the agreed requirements pass and every remaining exception has an owner. The result is a decision your team can explain later, with a practical implementation plan ready to follow.
Bring your security question to Midland
Tell us which systems you need to protect and where investigations get stuck. We can review the AI Native SIEM offering against that requirement.
Review our AI Native SIEM and SOC platform or discuss your environment with us.
Sources and technical scope
Checked October 23, 2026. Product capabilities and supported integrations depend on the offered configuration. Planning examples below are evaluation guidance, not measured customer results.