AI Integration Services, Built and Tested by QA Engineers
We add AI features to your product and make sure they work: language models, chatbots, AI agents and AI search, tested the way we test any critical feature, so you ship AI your users can trust.
- One use case with clear value
- Working integration in your stack
- Evaluation, security and regression tests
- Monitoring and guardrails
What we build
- 01
AI chatbots and assistants
Customer support, onboarding or in-app help, connected to your data and your tone of voice.
- 02
RAG and AI search
Answers based on your own documents, knowledge base or product data, with sources.
- 03
AI agents and workflow automation
Agents that take actions in your tools: process requests, fill in data, trigger workflows, with human checkpoints where needed.
- 04
LLM features inside your product
Summaries, classification, content generation and data extraction, added to your existing app through APIs.
Why AI integration needs QA from day one
AI features fail in ways normal software does not. They can give wrong answers with confidence, leak private data, be manipulated with a clever prompt, or slowly get worse after a model update. Most integration vendors build the feature and stop there. We build it and test it, as one job.
How we test what we build
Accuracy
Evaluation sets with expected answers, checked on every change.
Hallucinations
Answers must be grounded in your data.
Security
Prompt injection, jailbreaks and data leaks, based on the OWASP Top 10 for LLM applications. See OWASP Top 10 testing.
Regression after model updates
Automated checks, so a new model version does not break what worked.
Performance and cost
Response time and usage under load.
Built by someone else?
Already have an AI feature? See AI & LLM testing.
How we work
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Discovery
We pick one use case with clear value and agree how to measure success.
-
Prototype
A working version on your data, tested against real questions.
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Integration
The feature goes into your product with monitoring and guardrails.
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Testing and release
Evaluation, security and regression tests run before and after release.
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Support
We monitor quality and update prompts, data and models as needed.
Why Test Squad
- QA engineers build it, so testing is part of the work, not an afterthought.
- A team of 30, working since 2023.
- Our in-house approach works with any programming language, so the integration fits your existing stack.
- Start with a free audit: we review your product and suggest where AI adds real value.
Tools we use
- Claude
- OpenAI
- LangChain
- Vector databases
- Vercel AI SDK
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Promptfoo -
Ragas
FAQ
What are AI integration services?
Adding AI capabilities, such as chatbots, AI search or AI agents, to an existing product, usually by connecting large language models to your data and systems through APIs.
Which AI models do you work with?
We work with leading commercial and open-source LLMs and choose based on your quality, privacy and cost needs.
Is our data safe?
We design the integration so your data stays under your control, use access limits and test for data leaks and prompt injection before release.
Can you test an AI feature that is already built?
Yes. That is our AI & LLM testing service.
How do you measure if the AI works well?
We build evaluation sets with real questions and expected answers and run them on every change, together with security and regression tests.
How do we start?
Get a free audit. We will review your product and suggest one or two AI use cases worth building first.
AI & LLM Testing 
Test Automation 
Performance Testing Let’s talk about your next release
Book a 30-minute call with our QA lead, or start with a free audit: a short report on the risks we see and where testing pays off first.