Two days. That's how long the full regression suite took to run before every release at a HVAC company that ships every one to two weeks. Sit with that math for a second: in a bad month, close to a third of the entire release cycle was spent just confirming that nothing had broken. Not building. Not fixing. Confirming.
Eight weeks after adopting no code test automation, that same regression suite runs in 50 minutes. Here's exactly how it happened and why the interesting part isn't the speed.
Why regression testing was eating the release cycle
One of our client builds sales software for the residential HVAC industry — dealer-facing quoting and distributor catalog management, all powered by a continuously updated database of equipment specs, warranties, and rebates from every major manufacturer.
That data-heavy architecture is precisely what made testing brutal. Dynamic location-based pricing, multi-tenant configurations, and catalog rules meant the number of test scenarios kept ballooning, and every one of them was checked by hand. A full manual regression pass took two days, and when defects surfaced late, releases slipped.
It's a familiar trap. Industry data shows automated testing cuts regression cycles from an average of five days to under one, and reduces overall testing time by 35–50%. Our client was leaving all of that on the table, not because they didn't want automation, but because they had no developers to spare for building it.
What does AI-powered test automation look like in production?
In production, AI powered test automation means three things: existing manual testers building automated tests without writing code, suites running automatically inside the CI/CD pipeline, and coverage that scales with the product instead of with headcount. The HVAC company's rollout hit all three in eight weeks. Here's the sequence.
Start with a proof of concept, not a contract
Rather than promising outcomes on a slide, the engagement began by automating five of their most complex end-to-end scenarios — the intricate, data-driven workflows most likely to break an automation tool. The PoC handled them, which settled the question that matters most: can this platform survive our application?
Let manual testers build the automation
This is the part most teams get wrong. Automation projects stall when they depend on scarce engineering time — 55% of teams cite skilled labor shortages as their biggest automation barrier. This HVAC company sidestepped it entirely: their existing manual testers started building automated tests on Sedstart's no-code automation platform from day one, using the same visual interface behind features like record and play. Within eight weeks, 100+ regression test cases covering business-critical journeys were fully automated — by the people who knew those journeys best.
Wire it into CI/CD from day one
The automated suites were embedded directly into the client's CI/CD pipeline, running on demand or on schedule across dev, staging, and production environments. Regression stopped being an event someone had to organize and became something that simply happens.
The results: a 94% reduction in regression time
The full regression suite now completes in 50 minutes instead of two days — a 94% cut. But the downstream effects are where the value compounds:
- QA engineers moved to exploratory and functional testing — work that actually requires human judgment
- Developers deploy with confidence, no longer blocked waiting on QA cycles
- Every environment gets identical validation, eliminating the "worked in staging" class of surprises
The direction matches the wider industry: in Testlio's 2025 automation statistics, 20% of teams report having replaced 75% or more of their manual testing effort — and our client's trajectory shows why that number keeps climbing. The full engagement details are in this HVAC test automation case study.
What happens after the first 100 test cases?
Momentum. The client has already expanded the engagement into functional test automation, with 200–300 additional test cases planned over the next six months. That's the pattern with AI-powered testing services done right: the first win funds the second, because time reclaimed from regression gets reinvested into coverage. Capabilities like Sherlock AI, which autonomously explores an application and generates test cases with zero scripting, make each expansion cheaper than the last.
The 50-minute release check
The client didn't hire automation engineers, rebuild their QA team, or pause releases to make this happen. They gave the testers they already had a platform that didn't require code, and eight weeks later the two-day bottleneck was a 50-minute checkpoint.
If your regression suite still runs on the calendar instead of the pipeline, see what your own 2-days-to-50-minutes story looks like.
Book a demo with the Sedstart team, or start a free trial and automate your first critical flow this week.
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