Is your AI responding safely?
Does it refuse harmful prompts? Does it hallucinate in ways that could hurt your users? Most teams don't test for this systematically.
QA & AI Safety
It works on your machine. Does it work everywhere else?
Developers ship fast and test rarely. In an AI product, that's no longer just a quality problem - it's a safety problem. We set up end-to-end testing for both your software and your AI layer.
2x
Testing layers - software and AI
0
Existing QA framework needed to get started
End-to-end
From unit tests to AI evals and monitoring
A New Problem
AI has added an entirely new layer of testing that most teams aren't running.
Traditional QA checks whether your software works. AI testing checks whether your AI behaves - safely, consistently, and within guardrails. These are different problems that need different tooling and different expertise.
Can someone inject through your prompts?
Prompt injection is the new SQL injection. If you haven't tested for it, you haven't secured it.
How do you know if quality degrades?
Without evals and traces in place, a model update or prompt drift can silently break your product. You won't know until users complain.
Prompt injectionAI guardrailsSafety evalsAI monitoringRegression testingE2E automationBrowser testingUnit tests
What We Set Up
Full-stack testing. Software and AI.
We build the complete testing infrastructure your product needs - both layers, from scratch or on top of what you already have.
Software QA
Tried and tested. Fully automated.
Unit test framework
Comprehensive unit test coverage across your codebase with CI integration.
Browser and E2E automation
Automated end-to-end flows across browsers and devices using Playwright or equivalent.
Regression testing
Automated regression suites that run on every PR so nothing breaks silently.
Load and performance testing
Stress testing under real-world traffic conditions before you need it.
Continuous QA in CI/CD
Testing wired into your build pipeline so every deployment is gated on quality.
AI Safety and Testing
The layer most teams are missing.
AI guardrails
Input and output guardrails that prevent unsafe, off-topic, or harmful responses.
Prompt injection testing
Systematic testing of your AI's resistance to injection attacks and jailbreak attempts.
AI evals framework
Structured evaluation pipelines to measure and track AI output quality over time.
Tracing and monitoring
Full observability on your AI layer using LangSmith, LangFuse, or equivalent tooling.
Safety evals and fencing
Automated safety benchmarks that catch regressions in AI behaviour before they reach users.
Case Studies
AI shipped with the testing to back it up.
Client name withheld
Automating Patient Outreach at Scale with AI SMS + Voice
End-to-end design and engineering for a US healthcare outreach platform - multi-tenant, multi-language (90+), with AI auto-response, redetermination workflows, and full traceability through Langfuse for every AI decision.
100,000+ AI-generated SMS sent through the platform
Stitch (StitchCare)
Reimagining Post-Transplant Care Coordination with Stitch
Tequity has been Stitch's product partner from MVP through a strategic pivot into post-transplant care - building AI-powered care coordination tools that combine modular care plans, voice calling, and care-coordinator oversight of every patient response.
MVP shipped and pivot to post-transplant care delivered without losing velocity
Riverwalk Holdings
Powering AI-Driven Investment Intelligence at Riverwalk
Built an AI-driven monitoring platform that ingests data from Tracxn, K-Scan, LinkedIn, Medium and ~21,000 company links - then summarises, scores, and surfaces what the Riverwalk investment team needs to act on each day.
3 hours per day saved by Associates and Partners
ChargeZone
Building India's Largest EV Charging Network with ChargeZone
Tequity owns end-to-end product, design, and engineering for ChargeZone's consumer mobile app, including a booking-flow redesign that delivered a 12-15% conversion lift and India's first EV-charging loyalty program.
13,500+ charging points managed on the platform
Engagement Options
Set it up once, or keep it running.
One-time setup or ongoing QA partnership - both options available.
One-Time
QA and AI Safety Setup
We build the framework. Your team runs it.
- Audit of existing test coverage and gaps
- Unit, E2E, and regression test suite setup
- CI/CD pipeline integration
- AI guardrails and prompt injection testing
- AI evals and tracing setup (LangSmith / LangFuse)
- Handover documentation and team training
Ongoing Retainer
Continuous QA Partnership
We own testing so your engineers own product.
- Everything in QA Setup
- Dedicated QA resource on your team
- Test coverage on every new feature release
- Ongoing AI safety eval runs and reporting
- Monthly QA health reports
- Proactive catch of regressions before users do
From the Blog
Related Reading
AI Engineering
How to Evaluate LLMs Before Shipping to Production
Vibes-based testing breaks in production. Here's the evaluation framework we use before deploying any LLM-powered feature.
Rahul Nair
Co-Founder & Head of Engineering
Engineering
6 Things Vibe-Coded Apps Get Wrong Before They Hit Production
Vibe coding gets you to a demo fast. It rarely gets you to production. Here's what breaks between the two — and how to fix it.
Rahul Nair
Co-Founder & Head of Engineering
Engineering
Coding with AI: Shortcut to Success or Road to Mediocrity?
AI coding tools have genuinely changed what's possible for small engineering teams. But they've also created new failure modes that weren't possible before.
Ajay Kumar
Co-Founder & Director
LET'S TALK
Ship fast. Ship safely.
We set up the testing infrastructure so your engineers can keep building without breaking things.