Security-first by design
We build voice agents and custom AI tools with practical guardrails—so you can ship measurable automation without taking on unnecessary risk.
A pragmatic security overview
This page summarizes the safeguards we typically implement. Your requirements may differ based on industry, data sensitivity, and deployment preferences.
Important: This is an overview of our approach—not a compliance attestation. If you need a vendor security questionnaire, we can respond during the sales process.
Our approach
1) Start with scope
- Define what the system will and will not do
- Identify sensitive data types (PII/PHI/PCI/internal-only)
- Agree on success metrics, failure modes, and handoff conditions
2) Minimize data
- Collect only what’s required to complete the workflow
- Avoid storing transcripts/audio unless explicitly needed
- Align retention to your policy and operational needs
3) Constrain access
- Use least-privilege credentials for integrations
- Separate environments (dev/staging/prod) when appropriate
- Apply role-based access to internal tools and dashboards
4) Make it observable
- Log key actions (what happened, when, and why)
- Monitor error rates, escalation rates, and edge cases
- Maintain QA/evaluation loops for conversational quality
Common safeguards
Data handling
- Data minimization: request only fields required for the task
- Redaction (when needed): mask sensitive strings in logs
- Retention: configurable windows for logs/transcripts
- Secure transport: HTTPS/TLS for data in transit
Access controls
- Least privilege: narrow-scoped API keys/tokens for CRM/helpdesk/calendar access
- Secrets management: keep credentials out of code; rotate keys when required
- Auditability: track which system performed which action
System design
- Human handoff: explicit escalation paths when confidence is low or policies trigger
- Policy constraints: disallow high-risk actions unless explicitly designed and reviewed
- Rate limiting + abuse controls: protect endpoints and form submissions
Reliability + QA
- Test cases: example-driven testing for critical flows
- Fallbacks: graceful handling when dependencies fail (CRM outage, calendar conflict)
- Post-launch monitoring: dashboards/alerts for drift and regressions
Deployment & data residency options
We’ll recommend a delivery pattern based on your risk profile, internal capability, and time constraints.
- Managed stack (fastest): rapid iteration using reputable cloud services
- Bring-your-own-cloud: deploy into your AWS/GCP/Azure account and align to your IAM, logging, and network controls
- Hybrid: keep sensitive systems internal while using external services where acceptable
AI-specific risks we plan for
- Incorrect outputs: mitigated by scope, retrieval grounding, and explicit handoff rules
- Prompt injection / data exfiltration: mitigated by input filtering, tool constraints, and least-privilege access
- Quality drift: mitigated by monitoring, evaluation sets, and iteration processes
- Voice-specific concerns: confirmations for critical details (names, dates, phone numbers), plus safe retries
FAQ
Will you sign an NDA?
Yes, typically.
Can you deploy into our environment?
Often, yes. We’ll align the architecture to your preferred cloud and security controls.
Do you store call recordings or transcripts?
Only if it’s required for the workflow and approved. We prefer minimal retention with configurable policies.
Can the agent take payments or handle highly sensitive personal data?
It can be designed to, but it changes the risk profile. We’ll recommend safer patterns (handoff, tokenization, or offloading to existing secure flows) depending on requirements.
Can you complete our vendor security questionnaire?
Yes—share it after the initial consult and we’ll respond with the details relevant to the proposed build.
Next step
Have security requirements? Let’s design around them.
Let's talk or reach out via the contact page.