Guardrails and Evaluation,
for the Agentic Era
Continuous evaluation, real time guardrails and pre production agentic testing. Made for agents, RAG and chatbots.
Available as a service, on your cloud or on prem
Real-time Protection
Block fraudulent, unauthorized and policy violating outputs in real time, preventing them from reaching customers.
Agentic Testing
Framework
Validate agents workflows across real world scenarios, multi step flows, reproduce failures with deterministic artifacts.
Contextual
Evaluation
Small language model judges based evaluation for unparalleled speed, accuracy at a fraction of the cost.
Accurate %
F1 score
Latency
Case Study: Grounding and policy adherence in customer support workflows
Overview
A mid market online investment firm uses an AI agent to handle client requests, such as checking account balances, provide portfolio performance summaries and retrieve current stock and interest rates. To scale automated support without adding execution risk, the firm partnered with Qualifire.
The challenge
To improve customer experience and reduce service costs, the firm expanded its AI assistant for self-service financial inquiries. Its AI assistant has access to balances, portfolio summaries and market data. That capability improved speed and scale, but it also introduced clear business risks: any inaccurate financial data could cause customer loss, regulatory exposure and reputational harm. They required automated workflows that were safe, auditable and repeatable.
Solution
Before launch, Qualifire’s Rogue agent stress-tested the AI assistant across thousands of real and adversarial customer scenarios, uncovering subtle vulnerabilities that traditional QA missed.Each failure was transformed into an actionable policy fix or prompt adjustment, tightening both model and workflow reliability.
In production, Qualifire’s lightweight SLMs act as contextual guardrails - validating user intent, verifying correctness and groundedness, and blocking unsafe responses in milliseconds.
Outcomes:
The investment firm expanded its AI self service confidently: information provided by the chat bot was grounded in reliable sources, high risk cases routed to humans and compliance gained repeatable, auditable evidence. All while keeping latency low and accuracy high.
Frequently Asked Questions
How does Qualifire integrate with our LLMs/agents?
We run lightweight judge models in-line; minimal code changes and connectors for common stacks (APIs…)
Is my data private?
Yes — we offer on your cloud, hybrid, and fully on-prem deployments
How do you avoid slowing production?
Qualifire’s small language models are built with production constraints in mind, delivering ultra-low inference latency and minimal resource overhead to preserve throughput while leading the industry on accuracy and latency benchmarks.
Security & Compliance at Qualifire
SOC 2 type: II Compliant – Independently audited against industry standards for security, availability, and confidentiality.
Data Protection by Design – End-to-end encryption (in transit & at rest) with strict access controls.
Tenant Isolation – Logical multi-tenancy and data segregation to ensure customers’ data remains fully separated.
Penetration Testing – Regular independent penetration tests validate and strengthen our security posture.
Disaster Recovery & Resilience – Redundant infrastructure and tested recovery procedures safeguard availability.
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