How Vervali Load Tests Shopify Stores Before Black Friday
How Vervali load tests Shopify and Shopify Plus stores before Black Friday: the Shopify rules, what gets tested, when to start and what it costs.
AI Business Solutions,
Built and Validated
Vervali builds document processing, forecasting and decision-support AI, with accuracy, bias and drift validation from day one. We report the trade-off when the fair choice and the accurate choice differ, and we do not decide your risk appetite. The standalone testing pack is on AI and machine learning testing.
150+ clients
450+ projects
275+ engineers
15+ years
ISO/IEC 17025:2017Accredited testing laboratory
CMMI Maturity Level 3The process is written down and repeats
ISO 9001:2015Quality management
ISO/IEC 27001Information security
Document Processing, Forecasting and Decision Support
Three kinds of AI we build, each validated from day one.
Document Processing
Extraction, classification and the exception a person still has to see. A fluent wrong extraction is still a fail, so accuracy and review load are checked together.
Forecasting
Held-out accuracy, calibration, and whether the forecast is still true after the world moved. Drift after launch is on data drift testing.
Decision Support
The decision a customer or an operator sees, and whether it can be defended. Bias and explainability are on AI bias and explainability testing.
Need the model built and validated in the same week?
Free Model ReviewChatbots and Customer Support Automation
AI that handles the routine conversation and hands the rest to a person.
AI Chatbot Development
Chatbots that give instant support and improve the user experience, validated for accuracy and safe refusals before they go live. See chatbot development.
AI-Based Customer Support Automation
Support that answers faster and more consistently, with the cases a person must handle routed to one. See customer support automation.
Challenges AI Can Fix
The business problems these builds are aimed at.
Manual Operations
Time-consuming repetitive tasks, and the human error that comes with them, handled by automation with exceptions kept for people.
Inefficient Use of Data
Predictive models that pull insight from historical data your team already holds but rarely uses.
Little Insight for Decisions
Reporting and decision support that give an operator a defensible answer, not only another dashboard.
Compliance With Regulations
Built with the rules in mind, and tested so the evidence a review asks for exists. We test controls and do not issue certificates.
Built for Your Industry
The same build-and-validate approach, applied to the work each sector actually does.
Fintech and Banking
Document extraction for KYC and lending, and detection models for identity review. See fintech and banking.
Healthcare and Life Sciences
Scheduling and document processing built with PHI handling in mind. See healthcare.
Retail and eCommerce
Personalised recommendations and demand forecasting, checked against real purchase history. See retail.
Insurance Tech
Document processing and decision support for quoting and claims, with the decision trail a review needs. See insurance tech.
HR Tech and Payroll
Automated processing of payroll and HR documents, with exceptions routed to a person. See HR tech.
Logistics and Fleet
Routing and delay prediction on live operations data, validated against real delivery history. See logistics.
Real Estate and PropTech
Property recommendations and lead scoring, tested so listings and leads match the data. See real estate.
Aviation and Travel
Forecasting for demand and operations, checked under peak load. See aviation and travel.
Build and Validate in the Same Engagement
Building the model and testing it are separate buys, and you can take either or both.
The Product Build
Document processing, forecasting or decision-support AI, with accuracy, bias and drift checked before it ships.
Validation of a Model You Have
Held-out accuracy, bias, drift and LLM output when the model exists and the buy is the test pack. See AI and machine learning testing.
Monitoring After Launch
Continuous checks and retraining when it is warranted, not reflexive. See AI model monitoring and retraining.
Model Validation
Independent validation of a model, with results a review board can read. See model validation testing.
Already know the intended use? A QA lead can scope the build.
Book a CallValidation From Day One, Not a Slide After Launch
What Vervali needs to start, and what you receive.
What We Need to Start
The intended use, the decision the model supports and a held-out set you control. Training code is not a prerequisite when the work is an endpoint.
Evidence for a Review Board
Feature attribution, worked examples and a model card. Findings come with the evidence a model review board will ask for.
Fairness and Drift
Fairness across groups is on AI bias and explainability testing, and drift after launch is on data drift testing.
Case Studies
Three Vervali AI builds, each saying what was built and what changed. Vervali built these models as well as tested them.
Financial services · KYC deepfake detection
Manual review was the bottleneck on identity. A detection model for know-your-customer cut that load: 70% less manual review at 75% detection accuracy. Accuracy, the review load and whether the model could be defended sat in the same pack.
70% less manual review 75% detection accuracyAI calling engine · lead qualification
An AI calling engine, built and validated by Vervali. After: 35% more qualified leads and a 28% shorter sales cycle. The checks were whether the engine actually qualified the lead, not a leaderboard score.
35% more qualified leads 28% shorter sales cycleOperations · real-time SOP image detection
A real-time image detection system for standard operating procedure compliance, built and validated by Vervali. The check was whether the system caught the SOP miss on the floor, not a demo reel of clean frames.
How an Engagement Starts
From one intended use to a model that ships with its evidence.
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01
Share the Use
Tell us the intended use, the decision the model supports and the data you can share, with access under NDA.
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02
Get the Build and Checks
We agree the build, the validation checks and the evidence a review board will need.
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03
Start With a Model Review
A free review of one model, for one hour, is the first look. Most engagements land at $25 to $49 an hour blended, and a build is quoted separately from a test-only pack.
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04
Ship With Evidence
The model ships with its accuracy, bias and drift checks passing, 9am to 1pm Eastern with delivery from India.
Frequently Asked Questions
AI can take over repetitive work such as data entry, document extraction, customer queries and routine decisions, and hand the exceptions to a person. We build the automation and validate its accuracy, so a fluent wrong answer does not slip through. A free model review shows which task to start with.
Finance, healthcare, retail, insurance, HR and payroll, logistics, real estate and travel all have document, forecasting or decision work that suits AI. The build is the same, and the validation changes with the sector. See our industries for how each one is covered.
Yes, including ERP and CRM systems, through APIs on the systems you name. The integration is tested the same way as the model, because a wrong field mapping is as damaging as a wrong prediction. ERP and CRM work is on ERP and CRM development.
We check held-out accuracy and calibration, bias and fairness, drift since training, explainability, robustness to malformed input and data leakage. Here that pack ships with the build. The standalone pack is on AI and machine learning testing. Findings come with evidence a review board can read.
We build with the rules you name in mind, such as GDPR or HIPAA, and test the controls and evidence a review will ask for. We do not issue certificates. Data access is agreed before anything is signed, and we do not copy production records into a test environment. See compliance testing.
Through encryption, secure APIs and regular security testing on agreed in-scope assets. Application and API attack work is scoped separately. We do not claim certified security staff. See security testing for how that engagement runs. A free model review shows what needs securing first.
Yes. A model is validated at a point in time, so we agree what to monitor after launch and when retraining is warranted rather than reflexive. A free model review shows what to watch. Ongoing support, updates and enhancements are on AI model monitoring and retraining.
Most engagements land at $25 to $49 an hour blended. Work is scoped to the use, the data and the checks you need, then quoted before we start. A build is quoted separately from a test-only pack, and a free review of one model shows the surface first.
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