Customer Support Agents

Runtime Protection enforces a strict grounding requirement: every response must be backed by content from your curated knowledge bases and must include inline citations to the specific policy document, section, or FAQ entry it draws from. When the retrieval engine finds no authoritative source for a customer question, the system blocks the completion entirely and routes the case to a human agent queue with the full conversation context attached. This prevents the bot from improvising answers about refund policies, warranty terms, or account rules that could create contractual liability.

Voice agents continuously monitor transcription confidence and intent classification scores throughout the conversation. When confidence drops below your configured threshold, the agent asks targeted clarifying questions rather than guessing. If ambiguity persists, it triggers a warm handoff to a human representative—or sends an SMS follow-up with a summary and callback link—before it can repeat incorrect totals or misrouted actions. The live rep receives a structured conversation summary via Observability, including the specific point where the bot lost confidence and the customer's original intent.

Our red teaming pipeline generates adversarial datasets tailored to your support domain—testing for prompt injection, social engineering, and policy manipulation specific to your product catalog and refund rules. Runtime guardrails then filter abusive language, refuse requests that violate your business policies, and flag suspicious sessions to supervisors in real time. You can lock high-value actions like promotional code generation, refund approvals, or account modifications behind mandatory human approval gates, ensuring that even a successful jailbreak cannot authorize financial transactions.

Runtime Protection maintains immutable, timestamped logs of every customer interaction, including the exact prompt sent to the model, the retrieved context used to generate the response, the final message delivered, and any guardrail interventions that modified or blocked content. Logs also capture consent states, required regulatory disclosures, and the specific policy documents cited. When a dispute or regulatory inquiry arises, your compliance team can export a complete, tamper-evident record of the conversation with a single API call or dashboard action.

Customer-facing bots require guardrails across three critical dimensions. Content guardrails prevent the bot from generating offensive, discriminatory, or legally problematic responses—even when customers attempt to provoke or manipulate it. Policy guardrails ensure every answer about refunds, warranties, pricing, and account actions aligns with your current business rules, preventing the bot from making unauthorized commitments. Escalation guardrails detect when a conversation exceeds the bot's competence—complex complaints, regulatory inquiries, or emotionally charged situations—and route to a human agent with full context before the interaction goes wrong.

Before deployment, our red teaming pipeline runs thousands of adversarial conversations against your bot, simulating the full range of customer behaviors: confused users, angry complainants, social engineering attempts, prompt injection attacks, and edge-case product questions. Each test conversation is scored for policy compliance, factual accuracy, tone appropriateness, and resistance to manipulation. The results produce a vulnerability report with specific failure modes and remediation steps, and the most effective attack patterns are converted into ongoing guardrail rules. Most teams run a final red teaming sweep before each major product launch or policy change to validate that the bot handles new scenarios correctly.