- Home /
- Industries /
- AI/ML software testing services
AI/ML software testing services
Testing for LLMs, recommendation engines, predictive models, and AI-enabled applications.
DeviQA provides AI/ML testing services for LLM applications, recommendation systems, classification models, and AI-powered products. Since 2010, we have completed 500+ QA projects for 300+ clients across more than 40 industries, supported by 300+ engineers. Our team evaluates output quality, hallucinations, bias, model drift, data quality, latency, security, and integration behavior. DeviQA is certified to ISO 9001, ISO 27001, and ISO 20000-1 standards.
Trusted by
Traditional QA was not designed for this
Conventional testing is built on a simple premise: same input, same output. AI breaks that premise entirely. Outputs are probabilistic. Models degrade silently post-deployment. And the cost of missed failures is measured in user trust, compliance risk, and revenue.
<20%
of enterprises feel confident validating GenAI behavior in production
~60%
of AI initiatives fail to scale due to validation and monitoring gaps
87%
of AI/ML projects fail due to poor data quality or undetected model drift
DeviQA AI Integrity Framework for AI/ML testing
The DeviQA AI Integrity Framework combines conventional testing with AI-specific validation. It addresses behavioral consistency, output reliability, drift and bias detection, and decision traceability across the technology stack.
DeviQA AI Integrity Framework
Behavioral baseline engineering
We define correct behavior through reference datasets, evaluation metrics, output ranges, and tolerance thresholds, accounting for probabilistic variation while flagging material failures.
Adversarial probing
We test prompt injection, jailbreaks, edge cases, boundary conditions, malformed inputs, and context shifts to identify AI failure modes before release.
Drift & bias detection
Automated monitoring compares input distributions, outputs, and model metrics against approved baselines, flagging drift, performance degradation, and bias for review.
Explainability & decision audit
We audit available inputs, outputs, confidence scores, retrieved sources, and tool calls to create traceable evidence for stakeholder and regulatory review.
The scope of DeviQA AI/ML software testing services
Testing across AI models, data pipelines, integrations, and production behavior.
LLM and generative AI testing
We test hallucinations, factual accuracy, prompt sensitivity, instruction following, output consistency, tone, refusal behavior, and safety boundaries.
ML model and pipeline validation
We validate training data, preprocessing pipelines, inference accuracy, prediction stability, edge cases, model drift, and pipeline integrity before and after model updates.
AI feature integration testing
We test AI-powered features across APIs, data flows, user interfaces, permissions, integrations, and fallback behavior within the complete product workflow.
Post-deployment monitoring and continuous QA
We monitor approved production signals, turn recurring failure patterns into test cases, and update quality checks as user behavior and model performance change.
AI audit and risk assessment
DeviQA audits your AI/ML testing approach, identifies gaps across models, data, integrations, and monitoring, and provides a prioritized remediation roadmap.
Abbott Laboratories is a global healthcare giant
90%
Test coverage
1.6k+
Test cases created
X18
Faster regression testing run
Compass is the first modern real estate platform
85%
Test coverage
2k+
Test cases created
2.5x
Faster regression testing run
Arklign is a dental practice platform
95%
Test coverage
5k+
Test cases created
3k+
Number of critical bugs logged
Tipalti is a payment automation platform
12
Years of cooperation
100%
Covered performance
2x
Faster regression testing time
Xola is a booking system for tours and attractions
90%
Test coverage
3.2k+
Automation test scripts created
1-2h
Time of regression
Experience the DeviQA difference
From initial consultation to full-scale QA implementation, we deliver results.
AI/ML testing cooperation models
Since 2010, DeviQA has provided staff augmentation, dedicated QA teams, and project-based outsourcing. Each model offers a different balance of client control and DeviQA ownership.
AI/ML QA staff augmentation
Add senior AI/ML QA specialists to your existing team while retaining day-to-day management.
Advantages:
Add model validation, LLM evaluation, and drift-detection expertise without running an internal recruitment cycle
Retain control over priorities, tooling, methods, and daily tasks
Scale testing capacity as your workload and AI roadmap change
Best for:
In-house QA teams adding AI/ML testing capabilities.
Dedicated AI/ML QA team
A managed team that works exclusively on your AI product and owns the agreed testing scope.
Advantages:
Retain knowledge of your models, datasets, prompts, integrations, and known risks
Maintain team continuity across sprints and model updates
Scale QA capacity without running additional internal recruitment cycles
Best for:
AI/ML products requiring ongoing testing without an internal QA function.
Project-based AI/ML testing
DeviQA manages the agreed testing scope for a defined AI/ML initiative.
Advantages:
Defined scope, deliverables, responsibilities, timelines, and reporting
DeviQA manages testing coordination, tooling, execution, and reporting
AI/ML testing methods, templates, and tooling adapted to your product and risks
Best for:
Teams launching, updating, or auditing an AI/ML product.
Why choose DeviQA for AI/ML software testing?
600,000+ project man-days delivered across 500+ QA projects for 300+ clients.
DeviQA owns the agreed AI/ML testing scope, deliverables, execution, and reporting.
DeviQA is certified to ISO 9001, ISO 27001, and ISO 20000-1 standards.
A free test trial lets you evaluate our AI/ML testing approach before a larger engagement.
Mid- and senior-level engineers combine software testing, automation, API, data, and AI model evaluation skills.
A 96% employee retention rate supports team continuity and long-term product knowledge.
A testing lab with 300+ devices supports AI-enabled web and mobile application testing.
Access to a community of 4,000+ QA engineers and testing specialists.
Your AI product moves fast. Your QA should too
DeviQA’s approach to AI/ML software testing
DeviQA uses a six-step AI/ML testing approach covering software functionality, data quality, model behavior, integrations, and post-release performance.
AI risk assessment
We identify AI-specific failure modes and align testing priorities with business risk.
Test strategy design
We define testing scope, datasets, environments, evaluation metrics, and acceptance thresholds.
Data quality validation
We check datasets for accuracy, completeness, consistency, bias, and data leakage.
Model behavior evaluation
We evaluate output accuracy, consistency, stability, and edge-case behavior.
Pipeline and integration testing
We test data pipelines, model APIs, product integrations, and deployment workflows.
Post-release monitoring
We establish checks for model drift, quality degradation, latency, and recurring failures.
Here’s what people are saying
about DeviQA
34 reviews
34 reviews
9 reviews
“It was so easy to integrate your people with us and we didn't have any problems.”
Janosch Greber
VP of engineering at RealTyme
“DeviQA has always brought us really high quality candidates for us to be able to seamlessly mesh into our team.”
Danny He
CEO and founder at Soapbox
“You guys have always been genuine, flexible and personable.”
Ryan Austin
CEO and founder at Cognota
“In fact, they have been a part of our success story, helping us grow from six workers 11 years ago to about 1200 workers now.”
Raanan Tauber
QA manager at Tipalti
“They can take my lack of knowledge and I can trust that they will be able to produce something of value.”
Ray Alde
Co-founder & cto at Arklign
“To me, that's above and beyond, I did not expect that to be so smooth and so easy.”
Mark Levine
Chief product officer at CYDEF
“They know what they're doing because the people that they send to us are quality people.”
Charles Chase
Chief technology officer at Returnmates
“There is also very good follow up on the engineers and the job they're doing.”
Olivier Mayot
Chief technology officer at SimpliField
Collaboration process overview
- 01
Initial contact. We start by understanding your testing needs and aligning them with your goals.
- 02
Assessment. Our experts analyze your current process and propose a tailored improvement plan.
- 03
PoC. Try a free proof of concept to see our capabilities in action.
- 04
Trial & evaluation. We conduct a trial phase and review the results together.
- 05
Contract & QA implementation. Once satisfied, we sign the contract and begin full-scale QA.
- 06
Flexible partnership. DeviQA offers scalable solutions to adapt to your business needs.
