Overview
SQAI Suite uses AI to intelligently orchestrate testing activities, resources and processes. It enables requirements analysis, test case generation, automation, and test data creation in minutes rather than weeks, positioning quality as a shared competitive advantage across product teams.
Key people
In the news
- Building and shipping a trustworthy, safe and valuable AI platform is a top priority and commitment to our growing userbase. Therefore we partered with QA Company. We asked them to thoroughly assess the quality of the product in a realistic customer setting. QA Company uses its proprietary #𝗘𝘃𝗮𝗹𝘂𝗮𝗶𝘁𝗲 methodology as a risk-based quality framework for AI systems, such as SQAI Suite. Evaluaite delivered practical insights on the quality and reliability of our platform and identified precise areas for improvement regarding AI
- Last week we argued AI's bottleneck in software delivery is context, not model quality. The most common reply: "we've connected everything with MCP, so we're covered." MCP is great. It kills the integration problem and it's now an open standard. But it standardises the connectivity, not the truth. An MCP server pointed at a Confluence page nobody has updated since 2023 will deliver that stale page beautifully. On time. Every time. Your agent doesn't know it's wrong. Neither does your staff in many cases... Freshness, provenance and
- Your documentation isn't missing. It's just wrong or out of date. Regenerating it with from scratch has never been the answer, you'll lose the structure, the formats, the links, the history. So teams don't do it. And the docs keep drifting. SQAI Suite DUM (Documentation Update Mode) changes that. Point SQAI at documentation you already have; Confluence, Notion, GitHub, SharePoint etc.,and it reads what's there, refreshes it from your real sources, and writes it back in place. Folder structure and formats intact, yet AI optimised for
- Everyone is shopping for a smarter model. The data says that's not the bottleneck 🥸 METR found experienced developers 19% slower with AI on mature codebases. Stanford's developer analysis shows gains collapse as complexity rises. Veracode found AI introduces rework and vulnerabilities in 45% of tasks, and that rate didn't budge across model generations. Global research has proven that is a context failure, not a capability failure. And your toolchain; Jira, Confluence, GitHub, Zephyr, spreadsheets..., structurally guarantees it...
- Small change, big difference in your day. Editing test cases from the SQAI Agent chat now happens in a sleek new drawer — no jumping screens, no losing the conversation you were having. ✏️ Steps, expected results and test data — all in one focused view 🔁 The same editing pattern everywhere in the platform ⚡ Fewer clicks between "that's not quite right" and "fixed" Because AI-generated test cases still need a human in the lead. The least we can do is make that part effortless. Watch it in action 👇 #SQAISuite #TestAutomation
- Some of your most useful context lives in files you can't paste into a chat. Now you don't have to. SQAI Suite lets you attach files straight into your conversations and put your own documents, specs and test data to work, grounding SQAI in your private context. 🔒 Encrypted 🧩 Session-isolated 🚫 Never used for AI training Analyze with full peace of mind. Watch it in action 👇 #SQAISuite #SecureByDesign #TestAutomation #QualityAssurance #AI #SaaS
- One in three production defects is born before a single line of code is written. Let that sink in🤯 Not in the code. In the analysis. In the backlog grooming. In the requirement that never mentioned the edge case. And here's where it connects to AI: agents are strongest on the happy path and weakest on edge cases..., exactly where those defects hide. Feed them vague requirements, and they'll confidently generate plausible test cases instead of valuable ones. That's why AI-ready docs need 5 things: 1️⃣ Specificity 2️⃣ Consiseness
- Your AI agents are only as good as the context you give them. So are your human colleagues. That's why SQAI Suite doesn't just generate documentation in the wild. It builds a living knowledge fabric for your entire SDLC. One single source of truth, optimized for every consumer: 🤖 For AI agents: Structured, machine-readable context your copilots and agents can actually reason over. 👩💻 For humans: The same knowledge, rendered clean and readable for the people in the loop. And getting there takes three steps, not three months:
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