AI Products
Our AI product suite, designed, built, and validated by our own AI quality practice, and configured to each engagement.
From resume pile to ranked shortlist, automatically
An end-to-end AI hiring platform: intelligent resume screening, skills-based candidate ranking, automated assessments, and interview scheduling, the same engine that powers our own Technical Hiring Services.
Your knowledge, answering customers around the clock
RAG-powered chatbots grounded in your own documentation and data, accurate answers with sources, seamless human handoff, and hallucination Testing built into every release. Deployed on web, WhatsApp, and in-app.
Testing that maintains itself
Our internal quality engine, productized: AI-assisted test generation from user stories, self-healing selectors that survive UI changes, and an LLM evaluation harness for teams shipping AI features of their own.
Ancient wisdom, delivered by modern AI
A full-featured AI astrology product: instant chart generation, personalized AI-guided readings, conversational predictions, and daily insights, engineered for scale and validated by our own AI Testing practice so every response stays grounded and consistent.
These are not speculative side projects. Each one started as tooling we needed for a client engagement, the thing that did not exist, that somebody was doing by hand every week, that was quietly costing more than anyone had measured. Once the same tool was useful on a third engagement, it became worth building properly.
That origin shapes what they are good at. They solve problems we have personally had, in workflows we have personally run, which is a narrower and more honest claim than a platform that promises to transform your quality function. Where a product is not the right answer for you, the services practice usually is, and we will say which is which.
Everything here goes through the same assurance we sell. Conventional coverage across the sixteen Testing disciplines where it applies, functional, API contract, accessibility, performance, and, for anything with model output in the loop, the full AI evaluation practice: a golden dataset, an evaluation harness scoring accuracy, grounding and refusal behaviour, and CI thresholds that fail a build when quality moves the wrong way.
It would be difficult to argue otherwise. A company that sells AI Quality Engineering and ships an AI product judged by spot-checking would be making our own case against us.
Request a demo and a Senior Engineer will walk you through it against your own use case rather than a scripted happy path, including the parts where it does not fit, which is usually the more informative half of the conversation. Demos are NDA-protected, and nothing you share during one is used elsewhere.
If what you actually need is the capability rather than the product, that is a shorter route: embedded Engineers bring the same practice inside your team, and corporate training leaves the skill with your people. We would rather point you at the right one of those three than sell you the one with a licence attached.
Keep reading
The practice and the people behind these products.
Questions
Straight answers, written the way we'd say them on a call.
Still curious? Talk to usA 30-minute walkthrough of any platform, with your use case, not a canned demo.
16+
Years QA leadership
16
Testing disciplines
6
Markets served
1
Business day to reply
Tell us where quality hurts
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