Assess
We review your AI system, how it's built, where it's used, and where failures would hurt most.
AI System Testing & Evaluation Services
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Our AI evaluation and system testing services help you launch LLM apps, RAG assistants, and AI agents that work reliably, then keep them accurate as models, prompts, and data change. We combine automated AI testing with expert human review, so you catch problems before your users do.
What is AI Evaluation?
AI evaluation is the process of measuring how well an AI system performs against clear, agreed standards for accuracy, safety, and consistency. Unlike traditional software, AI can give a different answer to the same question each time. So one passing test proves little; quality has to be measured across many runs, real user scenarios, and edge cases.
Outputs vary. The same prompt can produce a correct answer today and a wrong one tomorrow.
Models and data drift. Provider model updates, new documents, and changing user behavior slowly shift quality.
Small changes break things quietly. A prompt tweak or model swap can fix one issue and create three others nobody notices.
Our AI System Testing & Evaluation Services
LLM Output Evaluation
We score your model's answers for accuracy, relevance, completeness, and tone against criteria built around your users and use case, across repeated runs, not one-off spot checks.
Security & Vulnerability Assessment
We assess your AI applications for security weaknesses, including prompt injection, sensitive data exposure, insecure integrations, and access-control gaps. Our testing identifies vulnerabilities across your LLMs, RAG pipelines, and AI agents, helping you reduce security risks and protect your systems, data, and users.
RAG Accuracy & Hallucination Testing
We check that your assistant retrieves the right documents and answers only from them, catching confident but unsupported answers before they reach customers.
AI Agent Testing
We test how your agents plan, call tools, complete multi-step tasks, and recover from errors, so autonomous workflows finish correctly and stay within their limits.
Safety, Bias & Adversarial Testing
We probe your system with prompt injection, jailbreak attempts, and edge cases to find data leaks and biased responses.
Regression Testing & Production Monitoring
We re-run your evaluation suite on every prompt, model, or data update and monitor live performance, so quality drift is flagged before it becomes a support ticket.
Industries we Support
Industries We Support
SaaS & Technology
Reliable AI features, copilots, and agents that ship faster without breaking.
FinTech
Accurate, auditable AI answers where errors carry financial and compliance risk.
Healthcare
Safe, grounded responses that never go beyond what your sources support.
E-commerce & Retail
Support bots and shopping assistants that stay on-brand and correct.
EdTech
Tutors and training assistants that give accurate, age-appropriate answers.
Legal & HR
Knowledge assistants that cite the right documents and protect sensitive data.
WHy us
Advanced AI Evaluation Solutions Offered by Whizzbridge
Custom Evaluation Datasets & Success Criteria.
Public benchmarks don't reflect your users. We build test sets from your real queries, documents, and edge cases, and define what a "good" answer means for your product before testing starts.
Automated Evaluation Pipelines.
We set up automated scoring, including LLM-as-judge checks, inside your CI/CD workflow, so every release is tested at scale without slowing your team down.
Expert Human Review.
Automated scores miss nuance. Our reviewers check tone, context, and domain accuracy, and calibrate the automated checks so they stay trustworthy over time.
Model & Prompt Benchmarking.
We compare models, prompts, and retrieval setups side by side on quality, latency, and cost, so you can choose the right option with evidence instead of guesswork.
AI Analysis & Continuous Improvement.
We trace failures to their root cause, whether it's the prompt, retrieval, data, or model, and turn findings into clear fixes that improve performance with each release.
Our team
What Makes Whizzbridge Team So Special?
Product Owners.
Digital product managers and scrum product owners with extensive expertise in diverse industries, including banking, healthcare, e-commerce, and more.
Developers.
Senior software engineers, coders, and architects proficient in a wide array of technologies and frameworks.
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Business Consultants.
Highly skilled business consultants and strategy and operations specialists are adept at navigating various business types and sizes.
Quality Assurance Experts.
Seasoned QA engineers proficient in manual and automated testing, along with other quality assurance techniques, ensure the highest product quality and reliability standards.
UX Designers.
Talented UX designers are dedicated to creating seamless and user-friendly experiences, enhancing the overall design and usability of your digital products.
how we work
Our AI Evaluation Process
01.
02.
Define Success
We agree on measurable quality criteria and risk thresholds with your product and engineering teams.
03.
Build the Test Suite
We create evaluation datasets, automated checks, and human review guidelines tailored to your use case.
04.
Test & Analyze
We run the evaluation, report what's failing and why, and prioritize fixes by impact.
05.
Monitor & Improve
We keep testing every update and tracking live performance, so quality improves after launch instead of drifting.
HIRE US
AI System Testing Experts
Partner with Whizzbridge's AI evaluation experts to test, monitor, and improve your LLM apps, RAG assistants, and AI agents. From your first evaluation baseline to ongoing regression testing and AI analysis, we help you launch with confidence and keep getting better after release.
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FAQs
What is the difference between AI testing and AI evaluation?
AI testing checks whether specific behaviors work, such as a tool call, a safety guardrail, or a known edge case. AI evaluation measures overall quality across many runs and scenarios against your success criteria. We combine both for a complete picture.
Why does an AI system need testing after launch?
AI outputs vary, provider models change, and your data keeps growing. Each prompt or model update can quietly break answers that used to work. Ongoing regression testing and monitoring catch these issues before users do.
Can you evaluate an AI system you didn't build?
Yes. We evaluate LLM apps, RAG assistants, and AI agents built in-house or by other vendors, on any major model or provider. You keep full ownership of your models, data, and IP.
Do you use automated or human evaluation?
Both. Automated evaluation gives speed and coverage on every release. Expert human review handles nuance, domain accuracy, and tone, and keeps automated scoring calibrated.
How long does an AI evaluation engagement take?
A baseline evaluation typically takes a few weeks, depending on your system's complexity and how many use cases are in scope. Ongoing monitoring and regression testing then run alongside your release cycle.
testimonials
What Clients say about our team
Read some of our great experiences with our clients
"I had live access to the design files, and we had short stand-ups that the team was always well prepared for."
Gavin Doughty
CEO, RespondAbility
"They were excellent from a project management perspective."
Andrew Hall
CEO, Sumdog
"They were responsive to changes that came up mid-project and still kept on pace."
Mark Schlake
CEO, Club Passports
"They are willing to stick it out and keep looking for engineers that match our strict expectations."
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Ron Taylor
CTO, Studies Weekly
"The flexibility, friendly communication, price, support, and deliverables are incredible."
Michael Umschlag
VP of Engineering, Market Research Company
"This team did a great job of climbing into our heads."
Spencer B.
Director of Product, Nursing Home Analytics Platform
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