Service · Quality Engineering
Catch the defect before your users do.
The quality layer that lets you ship faster without shipping bugs — AI-built automation, regression, performance, and API QA, wired into your CI.
Every change, gated
Defects caught in minutes, not by customers
The real problem
Why QA becomes the bottleneck the faster you try to move.
Most teams test the way they always have while trying to release the way frontier companies do. Coverage is thin and hand-written, so it can't keep up with the change rate; releases get batched to stay safe, and the defects that slip through reach customers instead of a suite.
The cost is not abstract — and good testing catches the defect early, when it costs a fraction of a production incident.
US cost of poor software quality in 2022 — the price of catching defects late, in production, instead of early.
Of that locked up as technical debt — defects and shortcuts that compound into a permanent drag on delivery.
Where it pays off
Where testing actually pays — and what each kind of QA delivers.
Distinct disciplines, each guarding a different failure mode.
Test automation
Automated unit, integration, and end-to-end suites cover the paths that must hold every release, running on each change.
Defects caught in minutes, not by customers
Regression testing
Durable coverage of everything that already works, expanded as the product grows, so new code can't silently re-break old behavior.
Lower defect-escape rate as the codebase ages
Performance & load testing
Realistic traffic run against the system to surface slow queries and the breaking point before real volume finds them.
Protected uptime on the days that matter most
API & contract testing
Suites that exercise contracts, auth, and error handling at the service boundary, so integrations don't break silently when a payload shifts.
Fewer integration failures, safer service changes
Manual & exploratory QA
Skilled human testing that probes what a script never thinks to check — confusing flows, broken states, odd real-world use.
Usability & edge-case defects automation can't see
AI-assisted generation & triage
AI generates coverage for new code, analyzes gaps, and triages failures so engineers chase real breaks, not flaky noise.
Far broader coverage for the same team
As of June 2026 · revisit quarterly
What disciplined testing does to delivery — the measured impact.
Independent industry findings — never Silicon Prime's own client results.
AI accelerates coverage. Of quality-engineering leaders report faster test automation from generative AI — the leverage behind AI-built suites.
It's mainstream now. Of organizations already use generative AI in QA — AI-assisted testing is standard practice, not an experiment.
Continuous testing wins. Teams that meet their reliability targets are 3.7× more likely to test continuously — one of DORA's strongest predictors of delivery performance.
Twice-a-week releases, zero critical defects — four years. A 200+ location chain (BJ's Restaurants) under the Aegis AI process. Testing made faster releases safer, not riskier.
What's included
What our software testing services cover.
Coverage that holds your releases — not a test folder everyone ignores.
QA strategy & risk-ranked test plan
We find the highest-risk gaps and write a test plan ranked by risk, not by what's easy to automate — an honest map of what to fix first.
Test automation wired into CI
We build unit, integration, and end-to-end suites and wire them into your pipeline so a bad merge is blocked before it ships, not found a day late.
AI-generated regression coverage
Our patent-pending Aegis AI process generates and maintains regression coverage past what a team could write by hand, kept current as the product changes.
Performance, load & API testing
We model realistic traffic to find bottlenecks before peak volume does, and cover service contracts, auth, and error handling so integrations don't fail silently.
Manual & exploratory QA
Skilled human testers probe the flows and edge cases scripts miss — usability and state bugs that only surface in real use.
Reporting, docs & team handover
Defect and coverage dashboards, the full suite in your own repos, and a team trained to run and extend it after we step back.
What you get — all assigned to you under full IP transfer
How it runs
How a QA engagement runs.
One accountable lead, fixed scope, no handoffs — the model behind all our AI development work.
STEP 01
Assess
Audit current coverage, release process, and defect history; rank the highest-risk gaps.
Output: a prioritized test plan & a quality baseline
STEP 02
Automate
Build the automated, regression, performance, and API suites against that plan, in your own repositories.
Output: a suite covering the flows that matter most
STEP 03
Integrate
Wire the suites into your CI/CD so they run on every change and gate releases, results visible to the whole team.
Output: a pipeline that blocks defects before they ship
STEP 04
Sustain & hand over
Maintain coverage as the product moves, report escape rate and pass rate, and train your team to own it.
Output: a durable quality layer & a team that runs it
The proof
A 200+ location business shipping at zero critical defects.
Our clearest evidence is BJ's Restaurants — a 200+ location chain whose software is critical to daily operations. We applied the Aegis AI process: AI code review, regression prevention, and test-coverage insight on every change.
Across four years and ongoing, release cadence moved from every two weeks to twice a week — with zero critical defects the entire time. Testing made faster releases safer, not riskier.
Silicon Prime is a Stanford-rooted Responsible AI lab, founded 2011, run by founder Kelvin Tran — 20+ years of production engineering, personally accountable for every engagement.
Why run your QA with us.
We proved this exact discipline at scale. Twice-a-week releases with zero critical defects across four years at a 200+ location chain (BJ's).
AI-built coverage, not hand-cranked suites. Our Aegis AI process generates and maintains regression coverage past what a team writes by hand, kept current.
Founder-led, one accountable lead. No account managers, no offshore handoff — the person who scopes the coverage answers for the escape rate.
Built to transfer. Every test asset, dashboard, and runbook is assigned to you, and your team is trained to own it.
Where it lands first
Where rigorous testing matters most.
Fintech
Payments and fraud paths where a single escaped defect is a financial or compliance event.
Fintech software →Healthcare
Patient-data and clinical workflows inside HIPAA-compliant architectures, where correctness is a safety requirement.
Healthcare software →Multi-location & enterprise ops
Software-critical chains where a bad release hits hundreds of sites at once and regression coverage stands between a change and an outage.
Operations platforms →Questions buyers ask before they hire.
Thirty minutes · no pitch deck
Ready to ship faster without shipping bugs?
Bring your codebase and release process — we'll find the highest-risk gaps, tell you honestly where coverage pays off first, what it takes to wire it into your pipeline, and what it costs.