Self improve the quality of voice & chat AI support agents
THE STAKES
A bad conversation isn’t just a bad experience. It’s lost revenue.
In customer support, an AI agent failure means wrong answers, broken promises, and customers who leave. A single bad interaction can turn a routine ticket into a churned account — or a screenshot on social media.
Wrong answers and false promises
An agent that hallucinates a policy, invents a discount, or promises an unavailable refund creates commitments your team then has to honor — or walk back.
Brand and tone failures
Your agent speaks with your brand’s voice on every interaction. Off-tone, dismissive, or unsafe responses erode trust at scale — and they’re rare enough that spot checks miss them.
Broken workflows
Returns, refunds, order changes, and escalations are multi-step workflows. One broken step strands customers mid-journey and drives repeat contacts.
Missed escalations
Furious customers, legal threats, and safety issues must reach a human. Escalation paths have to be tested, not assumed.
HOW BLUEJAY HELPS
Engineer trust into every support conversation
AI agent QA combines simulation — testing an agent against thousands of realistic scenarios before launch — with observability, the continuous monitoring of live conversations in production. Bluejay does both, and closes the loop by turning what it finds into fixes via self improvement.
COMPLIANCE & TRUST
Enterprise-grade trust for support AI
Bluejay is SOC 2 Type II certified and operates as an independent trust layer between your organization and your AI agents — with your own policies enforced as evaluation criteria.
Your policies, enforced
Define custom evaluation criteria from your own help center and policy docs — Bluejay scores every conversation against them.
SOC 2 Type II
Bluejay’s security controls are independently audited on an ongoing basis — not just at a point in time.
Works with your stack
Bluejay is vendor-neutral and sits alongside whatever platform your agent runs on — no rip-and-replace required.
Independent by design
Bluejay doesn’t build or sell AI agents. As a neutral QA layer, its evaluation of your agent has no conflict of interest.
USE CASES
Govern and self-improve all support conversations
Bluejay works with support agents across commerce, SaaS, marketplaces, and consumer services — whether you built them in-house or run them on a vendor platform.
Order status and changes
Simulate order-status, order-change, and cancellation conversations — then monitor those flows in production.
Returns and refunds
Test that agents follow refund policy exactly — no invented exceptions, no broken handoffs.
Billing and subscriptions
Validate plan changes, proration answers, and cancellation flows against policy-specific edge cases.
Troubleshooting and how-to
Catch wrong or outdated product guidance before it reaches customers, and keep answers synced to your documentation.
Escalation to human agents
Verify the handoff triggers on anger, risk, and complexity — with full context passed to the human agent.
Peak-season readiness
Load test at holiday-scale volume before it happens, so containment and quality hold when it matters most.
