Case study A An Australian not-for-profit serving elderly clients # Consent that is captured the same way, every time. Every incoming client hears the service agreement in plain language, gives an explicit yes or no, and leaves a timestamped record without a staff member making the call. [Talk to us about consent capture that holds up as evidence ](https://www.aixccelerate.com/talk-to-us?cta=Talk+to+us+about+consent+capture+that+holds+up+as+evidence&source=%2Fcase-studies%2Fvoice-consent-capture)[All proof stories ](https://www.aixccelerate.com/case-studies) Engagement Voice AI worker BuyerCompliance / Risk / Operations Industry and geographyHealth and social services. Australia. Evidence labelAnonymized delivery evidenceClient identity is withheld pending reference permission. Handling-time and volume figures will be published when they are verified. The situation ## The consent call was both the bottleneck and the compliance artifact. Every incoming client, most of them elderly, had to be taken through a formal service agreement and give verbal consent before records could be activated. Staff did this one call at a time. Intake volume made the queue unscalable, and the quality of the explanation changed with whoever made the call. The consent is the compliance artifact. Inconsistent capture or weak documentation means the organization carries the risk. What we built ## A voice AI worker that completes the evidentiary chain. An outbound voice AI worker calls the client, reads the full service agreement in plain language pitched for an elderly listener, pauses for comprehension, and captures an explicit yes or no. The conversation is not the end of the job. On completion the worker writes the outcome into the organization's SharePoint portal and other downstream systems, so consent is captured, timestamped, and filed without a human touching the record. - Call 01Outbound voice worker places the consent call - Explain 02Full agreement in plain language - Capture 03Explicit yes or no. Not a vague acknowledgment - File Outcome written to SharePoint and downstream systems The worker calls, explains the agreement, captures an explicit response, and files the record. Why they chose AI Xccelerate ## They needed a compliance record, not a voice-bot demo. 01 The differentiator was the evidentiary chainConsistent script delivery, a captured response, and an auditable record. The problem was treated as compliance work from the first design decision. 02 The last mile is the work that removes staff loadMost vendors stop at the conversation and hand back a transcript. This worker writes into SharePoint and completes the downstream record actions. 03 The listener was designed for, not only the buyerPlain-language delivery tuned for elderly clients addressed the real anxiety about automating a sensitive conversation with a vulnerable population. The value delivered ## Identical conversations. Defensible records. Staff time returned to judgment. Every consent conversation is delivered the same way. Every response is captured in a form that can be inspected. Staff time goes back to work that needs judgment. A manual intake bottleneck is removed without accepting more compliance risk: the trade most compliance leaders assume is unavoidable. Metric reserved Average handling time, before and after Reserved. Will be published when the baseline and post-deployment method are verified. Metric reserved Monthly consent volume Reserved. Will be published when the operating volume is confirmed for public use. Who this is for ## This story is for leaders who own disclosure, consent, and intake risk. The buyer is a compliance, risk, or operations leader who cannot trade documentation quality for speed. 01 ### Insurance Disclosure and policy confirmation calls that must be delivered consistently. 02 ### Financial services Consent, verification, and suitability confirmations that have to stand as a record. 03 ### Health and social services Intake conversations with vulnerable clients where the explanation is part of the duty of care. Next conversation ## Talk to us about consent capture that holds up as evidence. If your team still runs disclosure, consent, or confirmation calls one staff member at a time, bring us the workflow and the record you need to keep. [Talk to us about consent capture that holds up as evidence ](https://www.aixccelerate.com/talk-to-us?cta=Talk+to+us+about+consent+capture+that+holds+up+as+evidence&source=%2Fcase-studies%2Fvoice-consent-capture) Related stories ## The other three problems in this set. [Story B An AI software company in the Microsoft partner ecosystem Agentic expertise in the room, then on the platform. Founders / CTOs Read the story ](https://www.aixccelerate.com/case-studies/agentic-replatform-onyx)[Story C A healthcare software company operating EAP services Support that closes what it can and classifies what it cannot. Support / CX / COO Read the story ](https://www.aixccelerate.com/case-studies/support-triage-deflection)[Story D A Mexico-based promotional products company entering Spain and Italy Outbound that shows the prospect their own brand on the product. CRO / VP Sales / CMO Read the story ](https://www.aixccelerate.com/case-studies/hyper-personalized-outbound) --- **Canonical URL:** https://www.aixccelerate.com/case-studies/voice-consent-capture