Find more cases worth investigating. Spend less time finding the evidence.
Security systems already hold much of the evidence needed to investigate suspicious activity. But examining access-control records, locating CCTV and reconstructing events can require hours of manual work.
SIRV AI helps security teams identify investigation candidates, assemble relevant evidence and produce traceable findings for human verification.
Results from a customer sprint involving suspected access-card pass-back. Case-identification results were demonstrated during the sprint. Processing-time figures are estimates, not independently verified production results. Human verification was retained.
Your systems hold the evidence. Investigators still have to assemble the case.
Access-control systems record credential activity. CCTV systems capture footage. Incident-management systems retain reports. Each provides part of the evidence, but none necessarily establishes what happened.
Investigators often have to search records, reconcile timestamps, locate relevant footage and compare different accounts before deciding whether an incident requires action.
- Identify a suspected incident An access-control exception, report or other event prompts an investigation.
- Search operational records Examine credentials, doors, locations, dates and access-event histories.
- Locate corresponding CCTV Find footage for the relevant location and time period.
- Reconcile evidence Compare events, footage, reports and other records, checking for gaps or contradictions.
- Document findings and decide Establish what the evidence supports, what remains uncertain and whether further action is justified.
The difficulty is not simply finding a record. It is determining which records matter, how they relate and what the evidence actually supports.
Keep your security systems. Improve the investigation across them.
SIRV AI does not replace your access-control, CCTV or incident-management systems. It provides an engineered workflow to assess approved operational records, surface relevant evidence and support the investigator's review.
Investigators manually search and filter event records to identify potential cases.
Defined checks and AI-assisted assessment help identify candidates requiring review.
Analysts manually establish relevant locations, records and CCTV time windows.
Relevant records and supporting information are presented for focused investigation.
Evidence and findings must be brought together into a reviewable account.
The workflow helps structure the evidence, chronology, uncertainties and findings.
An investigator assesses the evidence and determines the outcome.
The investigator still verifies evidence, challenges interpretations and makes the consequential judgement.
Less manual evidence preparation. More focused investigative review.
From operational records to verified findings.
SIRV AI provides a pre-engineered investigation workflow, configured and validated for the customer's defined task and approved evidence.
Operational records
Approved access-control exports, relevant CCTV material and other authorised records are made available within the agreed scope.
Assessment and candidate identification
The workflow examines the defined evidence and identifies events or combinations of events requiring further investigation.
Supporting evidence
Relevant records, event sequences, gaps and uncertainties are presented for examination.
Investigator verification
An authorised investigator reviews CCTV and supporting records, tests interpretations and confirms or rejects proposed findings.
Recorded outcome and follow-up
Findings, supporting evidence, investigator decisions and required follow-up are documented within the agreed workflow.
The workflow is configured around available sources and customer requirements. Data access, integration methods and automation depend on the approved deployment scope.
What the customer sprint demonstrated.
SIRV tested an AI-assisted investigation workflow with a UK government research organisation. The task was to identify suspected access-card pass-back using anonymised access-control records and supporting CCTV images.
What was tested
The workflow assessed anonymised access-control records, surfaced suspected pass-back candidates and supported human examination of the corresponding CCTV evidence.
What was demonstrated
The evaluation reproduced the valid cases identified manually and found four further valid cases. Findings could be examined against the relevant operational evidence.
What the results do not establish
The sprint did not establish universal detection accuracy, independently verified production time savings or performance across every type of security investigation.
The improvement in case identification was demonstrated during the sprint. Processing-time comparisons are estimates. Cases were subject to human review, and identifying a suspected access-control exception does not establish wrongdoing.
Read how AI can support an unauthorised-access investigation
AI identifies candidates. Investigators make judgements.
An unusual access event is not proof of an unauthorised entry. A credential record does not establish who physically passed through a door. An apparent CCTV match may require further examination.
SIRV AI supports
- Locating potentially relevant events.
- Reconciling approved operational records.
- Assembling evidence for review.
- Highlighting gaps and uncertainty.
- Preparing traceable findings.
Investigators remain responsible for
- Verifying footage and supporting evidence.
- Testing alternative explanations.
- Confirming identities where justified.
- Assessing the significance of findings.
- Approving conclusions and follow-up.
Where the evidence is missing, contradictory or insufficient, the workflow should surface the uncertainty rather than present an unsupported conclusion.
Why buy an engineered investigation workflow?
General AI platforms can help organisations develop investigation tools. But developing a prompt or prototype is different from establishing a reliable operational process.
An organisation building internally must also design, test, control and maintain the complete investigation workflow.
Select approved systems, data fields, time periods and reliable source material.
Establish checks, exception handling, review stages and the required outputs.
Account for missing records, conflicting timestamps, incomplete CCTV coverage and ambiguous events.
Test representative cases, missed findings, incorrect candidates and reviewer outcomes.
Preserve supporting evidence, reviewer decisions and required follow-up.
Respond to changes in operational systems, procedures, data and AI behaviour.
SIRV AI provides a pre-engineered workflow that is configured and validated against the customer's investigation process, reducing the need to design and prove an equivalent solution internally.
Where SIRV AI fits.
The strongest starting point is a defined, evidence-heavy investigation that can be assessed against an existing manual process.
Demonstrated investigation workflow
- Suspected access-card pass-back.
- Access-control event reconciliation.
- CCTV-supported human verification.
- Identification of additional valid cases.
Further applications to evaluate
- Suspected unauthorised access.
- Event chronology reconstruction.
- Access-control and CCTV reconciliation.
- Broader incident and internal investigations.
Applications beyond the demonstrated sprint require assessment and validation against the organisation's own data, processes and investigation requirements.
Test SIRV AI against your investigation process.
Start with one defined investigation task. We can review how it is currently performed, demonstrate the workflow using anonymised examples and agree whether a structured sprint would provide useful evidence for a deployment decision.
A sprint can assess case identification, processing effort, evidence quality, exceptions and the role of human review against your existing process.
SIRV is a UK technology company providing pre-engineered, validated AI workflows for safety, security and resilience teams.
