Why
Vervali?

Why Vervali?

Data Security

Protecting digital information from unauthorized access, theft, or corruption.

Targeted Testing

Identifying specific areas of the website or application that are most critical or vulnerable to errors, and focusing testing efforts on those areas.

-30% Reduce Bug Cost

Through effective quality assurance practices, such as implementing automated testing, conducting regular code reviews etc.

Focused on Business goals

Aim to maximizing the website's potential to drive growth, increase revenue, and achieve other key performance indicators (KPIs).

-20% Testing Time

Through prioritizing testing efforts based on risk analysis and streamlining the testing process.

Risk Based testing

Involves identifying and prioritizing potential risks associated with a software application or system, and using this information to guide testing efforts.

Challenges into Triumphs

Turning problems into opportunities for growth and innovation

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AI model accuracy declining post-deployment

We implement continuous monitoring and retraining pipelines to maintain high accuracy and adapt to evolving data patterns.

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No visibility into feature or label distribution changes

We use drift detection tools to monitor changes in feature or label distributions, ensuring consistent model performance.

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Business-critical predictions affected by silent drift

We deploy real-time monitoring to detect and address any subtle changes in data that may impact business-critical predictions.

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Lack of real-time model monitoring in MLOps workflows

We integrate real-time model monitoring into your MLOps workflows, enabling quick detection and response to performance degradation.

Frequently Asked Questions FAQs

It’s the process of detecting changes in model input data that can affect prediction quality and model relevance over time.

Even slight shifts in data distributions can reduce model performance significantly, causing incorrect outputs.

Yes. We monitor input distributions (data drift) and output relationships (concept drift) in real time.

Continuously. We set up automated tools to track drift daily, hourly, or based on your prediction frequency.

We support NLP, classification, regression, CV, LLMs, and time-series models across platforms.

Yes. We integrate with AWS SageMaker, GCP Vertex AI, Azure ML, and other popular MLOps tools.

Yes. Our team provides detailed remediation plans, including retraining triggers and validation strategies.

Featured Insights

Embracing Accessibility

Vervali was commissioned to audit, identify and remedy over 2,000 URLs across all client platforms and solutions in accordance to the WCAG 2.0 guidelines with the objective to achieve AA Level of the 508 certifications.

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Automate Optimize and Drive Profitability

The offer loading and IP whitelisting was a process that was managed internally by our client. When they struggled to manage the increased volume, they reached out to us for help with manual data entry. Vervali analyzed the entire manual process and produced an automation plan and framework.

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A Bug Free Reward Program

To sustain an intensely competitive landscape of frequent flyers and loyalty programs our client was making every effort to engage & retain its customers by introducing increased benefits and new products. However, the introduction of these new changes without proper testing made their website more vulnerable and multiple defects.

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Digital Onboarding, Separation and Asset Management

With the increasing customer base, our client was enjoying great traffic and demand for their software. However, to sustain this increased growth, our client knew that they had to constantly upgrade their product. While they had introduced software to digitize the employee onboarding process. However, there were still many manual processes still in play. Our client needed a strategic partner, who can act as an extension of their team and help them digitize the manual processes.

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