Transform your business with GenAI-infused apps.
Protect it with Quality Engineering.

With Generative AI becoming more accessible, organizations are quickly adopting the technology to deliver new services, conquer new markets and optimize business processes. But applications infused with GenAI carry unique challenges and risks. Before you deploy, you need specialized Quality Engineering from a team of experts — like ours.

HOW WE CAN HELP YOU

We’ll turn tricky GenAI integrations into trustworthy experiences.

Large Language Models (LLMs), text-to-text applications and text-to-image apps are a complex amalgamation of multiple layers, which must all work together. Our rigorous testing and validation strategies will assure seamless integrations with your existing systems and mitigate risks:

  • Reduce toxicity and hallucinations (false or fabricated data).

  • Increase accuracy.

  • Protect data privacy in training data.

  • Remove regional cultural bias before global launches.

YOUR BENEFITS

Proactive brand protection and quality control that never quits.

We’ll optimize your business processes by assuring data sources, LLMs and seamless user interfaces. Our deep tech and domain expertise enables alignment with industry standards and your business goals.  

Higher data quality.

Enhance data quality through a comprehensive strategy that applies stringent criteria to examine data from source through distribution checks and outlier review.

Less bias.

Our “red teamingapproach tricks the GenAI model so we can proactively identify toxicity, cultural bias and stereotypes.

Faster releases.

Cut down release cycles with automated regression testing focused on end user experience, model performance and benchmarking.

Validation across geographies.

Avoid cultural bias, hallucinations and toxicity anywhere you launch with continuous LLM validation in multiple languages, powered in real-time by Qualitest’s dynamic fact database.

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OUR SOLUTIONS

Shift quality mindset left, right and center.

Deliver on the promise of GenAI with our comprehensive quality solutions. We’ll partner with you to build a customized Quality Engineering strategy for your GenAI-infused apps that leverages data quality assurance, model validation and customer experience testing.

Continuous data quality

Identify data quality issues early in the software development lifecycle (SDLC) by establishing standards from the start. Confirm data quality during transfer and transformation by leveraging our comprehensive data quality framework.

Content accuracy and automated validation

We’ll test your text-to-text or text-to-image applications for coverage, hallucinations, cultural bias, toxicity and accuracy of output, using prompts generated from various data sets and automating the output quality validation for time and cost savings.

Model graded output evaluation

We’ll compare your model output for metrics such as summarization, answer relevancy, hallucination, toxicity, bias and faithfulness, and we’ll implement continuous automation to benchmark KPIs against previous releases or industry models.

Red teaming against threat agents

Applying an adversarial lens to your AI system, we simulate probes and attacks with prompt engineering specialists and a prompt database, identifying harmful or objectionable output.

Localization testing and validation

We’ll test your GenAI-infused applications for global languages and regional context, ensuring your translations are regionally accurate and free from cultural bias.

A success story

Continuous Automation of Data Quality Validations Cuts Effort by 35% for Leading US News Agency

01—Challenge

The Client wanted to migrate to a digital asset management (DAM) system that was not based on meta data and enhance media search capabilities using AI-powered search. This new implementation opened up a new challenge, as it enabled users to search with Natural Language Processing (NLP) and the search results were not restricted to meta data tagging.

02—Solutions

Qualitest proposed a solution to analyze all search strings in production, leverage the search criteria and create new prompts to test the new AI engine. The production data was further expanded with localized search priorities and parameters. The solution also included automation of the data pipeline in the cloud and E2E integration testing.

03—Results

  • 100% on-time completion of the program.  Validation of the E2E cloud implementation of the application. 35% effort saved on Data Quality validations through continuous automation. 
OUR CAPABILITIES

What else can we help you with?

Let us know what your needs and requirements are and we’ll tailor a solution to make your life easier.

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