Post-sales AI platforms sit closer to customer data than almost any other tool a revenue team buys. They read CRM records, call transcripts, support tickets, product usage and contracts, and the newer ones do not just summarise that data. They draft emails, flag risk, update records and run workflows. That is exactly why they are useful, and exactly why a security review needs to go deeper than a checkbox questionnaire.
This guide is a practical checklist for CS leaders, CS Ops teams and security reviewers who are evaluating a post-sales AI platform. It covers what to ask about compliance, subprocessors, data protection, AI access and incident response, using Quivly's public Trust Center as a worked example of what good disclosure can look like.
Why Post-Sales AI Platforms Deserve a Closer Look
A typical post-sales platform connects to many of the systems your company already protects carefully. Once connected, it holds a combined view of every account: who the stakeholders are, what was said on calls, which tickets are open, how usage is trending and when the contract renews. That combined view is more sensitive than any single source system, because it puts commercial, personal and product data in one place.
AI adds two further questions. First, where does customer data go when a model processes it? Second, what can the AI actually do on its own? A platform that only reads data carries a different risk profile from one whose agents can write back to your CRM or send messages to customers. A good review treats both questions as first-class topics rather than footnotes.
Before you send a single questionnaire, write down which systems the platform will connect to, what kinds of data each one holds and which teams will use it. That simple data map makes every later question easier to answer and harder to dodge.
Start With Compliance Frameworks and Audit Reports
Compliance frameworks are the fastest way to understand how mature a vendor's security program is, as long as you read them carefully. The frameworks that come up most often for post-sales platforms are:
- SOC 2. An independent audit of a company's controls. A Type 2 report tests whether controls actually operated over a period of time, which tells you more than a Type 1 report that looks at a single point in time.
- ISO 27001. An international standard for running an information security management system.
- GDPR. The EU data protection regulation, relevant whenever the platform processes personal data about people in the EU.
- HIPAA. The US health data law, relevant if your customers or your own data touch protected health information.
The key is to separate what a vendor has achieved from what it is working toward. Quivly's Trust Center does this explicitly. It lists SOC 2 and HIPAA as compliant, and ISO 27001 and GDPR as in progress. Its resource library includes a SOC 2 Type 2 Report dated July 30, 2026. That kind of status-by-status disclosure is what you want from every vendor, because "in progress" and "compliant" mean very different things for your own commitments to customers.
When you review an audit report, check the date, the period covered, the systems in scope and any exceptions the auditor noted. A recent report with a clear scope is worth far more than a logo on a website.
Map the Subprocessors, Including LLM Providers
Subprocessors are the third parties a vendor relies on that may process your data. For an AI platform, this list matters more than usual, because it usually includes the cloud host, the database layer, monitoring and billing tools and, critically, the large language model provider.
Ask for the full list and look for three things:
- Which LLM provider is used. You need to know where prompts and customer data go when the AI processes them.
- What each subprocessor does. A billing tool and a model provider see very different data.
- How the vendor manages them. A vendor risk management policy shows that subprocessors are assessed, not just listed.
Quivly publishes its subprocessors in the Trust Center, including AWS and Google Gemini alongside monitoring, database and payments providers. It also lists a Vendor Risk Management Policy and data and privacy controls such as Vendor Privacy Risk Enforcement and a PII Inventory. Your own security team can then compare that list against the providers your company has already approved.
Check Encryption, Environment Separation and Network Controls
Product security controls are where a vendor shows how customer data is protected day to day. The questions here are familiar to most security teams, but they are worth asking directly:
- Is customer data encrypted in transit and at rest?
- Are production, staging and development environments separated, so test work never touches live customer data?
- What network boundaries sit between the internet, the application and the data stores?
- How are vulnerabilities found, prioritised and fixed?
- Is there a tested recovery plan if something goes wrong?
Quivly's Trust Center groups its controls into infrastructure security, organizational security, product security, internal security procedures and data and privacy. Under product security it lists Segregated Environments, Network Boundary Systems and Encryption Controls. Under infrastructure security it lists Vulnerability Management, Vendor Inventory and Recovery Plan Testing. A grouped view like this makes it easy to check each area off rather than hunting through a long PDF.
Ask How AI Access and Actions Are Controlled
This is the part of the review that traditional questionnaires often miss. A post-sales AI platform may connect to outside AI apps, run agents across your book of business and propose or make changes. Ask the vendor to walk through:
- Scope. Is data access limited to your organization, and to what each user is allowed to see?
- Authentication. Does each person sign in individually, so actions can be traced to a named user?
- Write access. Which actions can the AI take, and which need a person to approve the exact change first?
- Audit trail. Can you see what the AI looked at and what it changed?
Quivly's approach is a useful reference. Its hosted MCP connection uses a per-user sign-in so access stays scoped to each person's organization, and supported changes need write permission plus human approval of the exact change. If you want more background on how agents fit into daily work, see our guide to post-sales AI agents.
Review Policies, Incident Response and Continuity Plans
Controls only work if there are policies behind them and people who follow them. Ask to see the core documents and check that they are current. For a post-sales AI vendor, the essentials usually include:
- Information Security Policy
- Incident Response Plan and Policy
- Business Continuity and Disaster Recovery Policy
- Software Development Policy
- Vendor Risk Management Policy and Enterprise Risk Management Policy
- An architecture diagram showing how data flows through the system
Quivly's resource library lists each of these, with most policies dated February 01, 2026 and the architecture diagram dated May 15, 2026. For incident response in particular, ask how quickly customers are notified, who the contact is and how the plan is tested. Quivly lists both an Incident Response Plan and Incident Response Alerts among its internal security procedures, which is the kind of detail that shows the plan is operational rather than theoretical.
Run the Review Without Stalling the Rollout
A thorough security review does not have to add months to a purchase. A few habits keep it moving:
- Start with the Trust Center. Read what the vendor already publishes before sending a questionnaire, and only ask about the gaps.
- Request documents early. Audit reports and policies often sit behind a request access step, so ask for them as soon as the evaluation starts.
- Share your data map. Telling the vendor exactly which systems you plan to connect lets them answer precisely.
- Agree on AI guardrails up front. Decide which actions need human approval before the first agent runs.
- Revisit after go-live. Recheck compliance status, subprocessors and permissions as frameworks move from in progress to complete.
Treated this way, the security review becomes part of a good rollout plan rather than a hurdle in front of it.
If you are evaluating Quivly, the Quivly Trust Center is the place to start. It lists compliance status, controls, subprocessors and the documents your security team will want to request.
