April 13th, 2026 by Kendra Stansel
Following our recent SureWire™ beta launch event on April 8th, 2026, we have seen a significant surge of interest from teams eager to move their AI agents into production with confidence. Relying on inconsistent performance is an unacceptable risk that traditional, static QA tools are simply not built to manage, especially in high-stakes regulated industries. We developed SureWire to solve these challenges by scaling your expertise through specialized testing agents that proactively probe for adversarial risks and auditability.
To provide more clarity on our mission, we have compiled the 13 most common questions we received during the event about how the platform works.
Core Capabilities & Testing Scope
- What types of AI agents can SureWire test? In the current beta, SureWire beta is designed to test chatbots and conversational AI agents — either via your own public API endpoint or using Inflectra's built-in demo agents. Future versions will expand support to a broader range of agentic systems and deployment models.
- Can SureWire detect PII leakage? Yes, PII detection is one of SureWire's supported use cases in the current beta. PII is relatively well-defined and structured, making it a strong candidate for automated detection. SureWire can flag when an agent appears to be leaking personally identifiable information during testing, allowing teams to address it before production deployment.
- Can SureWire compare different AI models side by side? Yes — with some configuration. In the beta, you can connect two separate API endpoints (each using a different foundation model) and run the same test against both. This allows meaningful model comparisons. More streamlined, built-in model comparison features are planned for future releases.
- Is testing done entirely via prompting? Yes. You write a natural-language test plan, SureWire deconstructs it into an internal testing strategy, generates prompts to send to your agent, and evaluates the responses. The entire workflow is designed to be accessible to non-technical users, while still producing rigorous, repeatable results.
- Can SureWire be used to analyze documents not created by AI? SureWire is currently optimized for testing AI agents, not static document analysis. For requirements analysis and intelligent document processing, Inflectra's SpiraTest platform (including the recently announced Inflectra AI roadmap for Spira) may be a better fit.
Understanding Scoring & Metrics
- How does the Quality Score work? SureWire uses a qualitative scale of 0 to 100, where 100 represents excellent performance and 0 represents complete failure. Importantly, what "quality" means is specific to each test run — it's based entirely on what you ask SureWire to evaluate. Testing for refund policy accuracy will produce a different quality result than testing for polite tone, even against the same agent.
- How is the Confidence Score calculated? The confidence score reflects the variance across individual test outputs. If results are highly consistent — whether the agent consistently passes or consistently fails — confidence will be higher. A lower confidence score typically indicates a small sample size or mixed results. In the beta, the default number of test runs is limited, but increasing the volume of test executions will improve confidence levels.
Data Integrity, Privacy & Security
- Will SureWire get smarter over time with use? The team is actively exploring personalized learning capabilities, where SureWire can adapt its assessment weighting based on familiarity with your specific agents and testing patterns. However, data privacy and security are top priorities, and any such capability will be implemented carefully to ensure your data remains fully protected.
- Can SureWire validate agent responses against a database or document? Not in the current beta. This capability requires SureWire to have access to your data sources — raising important questions about security, data residency, and trust boundaries. The team is actively designing architectures that would allow this safely, potentially including deployment models where SureWire runs within your own protected environment.
- Does SureWire comply with specific AI risk or quality standards? The beta uses an internal quality model developed by the Inflectra team. Support for established regulatory frameworks and standards — as well as the ability to define your own risk criteria or integrate your organization's policy documents — is planned for future releases.
The Roadmap: Future Features & Scalability
- Does SureWire detect hallucinations? Hallucination detection is on the roadmap but is not yet available in the beta. Accurately detecting hallucinations requires grounding data — information SureWire can use to validate whether an agent's response is accurate. Expanding this capability is a key priority for the path to General Availability.
- Can I run multiple test scenarios in parallel? Not yet in the beta, but this is a planned capability. Future versions will support parallel test execution with weighted results feeding into an aggregated quality report.
- What's on the roadmap? The team has an ambitious vision for SureWire's first year and beyond, including: integration with CI/CD workflows, MCP server support for developer tooling (such as Kiro, Cursor and Claude Code), red teaming for security vulnerabilities, specialist agents for industry-specific risk frameworks, and more dynamic, iterative testing sessions that go deeper when problem areas are identified — similar to how a human red team would operate.
Ready to get started? Visit surewire.ai to join the beta and help shape the future of AI agent quality assurance. If you have any questions, do not hesitate to contact us.
