Service · Engineering
Performance that holds up under load — measured before, proven after.
We find the real bottleneck, fix it, and show you the before-and-after numbers on your own metrics — no rewrite, in 4–8 weeks.
Baseline → fix → prove
Measured on your real users
The real problem
Why a "rewrite" is almost never the answer to a slow app.
Slowness lives in a few specific places — an unindexed query, an N+1 pattern, a render-blocking bundle, a chatty API — never the framework. So a rewrite throws out the 90% that works and ships a stack that's still slow.
Left alone, it quietly bleeds revenue, search ranking, and cloud spend all at once. The fix isn't a rebuild — it's finding the real bottleneck and proving the gain.
Of conversions lost for every 100ms of added load time — the revenue a slow page bleeds, before SEO and cloud cost.
Of the app a rewrite throws away is the part that already works — the slowness was in a handful of fixable places.
Why we diagnose, not rebuild
Where it pays off
Where optimization actually pays — and what each one delivers.
A set of targeted interventions, each tied to a metric a buyer can read.
Core Web Vitals (LCP, INP, CLS)
Tunes the three metrics Google measures on real users.
Lower bounce, a healthier search position
Database & query tuning
Finds the unindexed lookups, N+1 patterns, and table scans that dominate response time, and fixes them at the data layer.
Lower latency on the slowest transactions, no rewrite
API & backend latency
Profiles service calls, adds the right caching, trims payloads, and cuts chatty round-trips.
Faster responses, more headroom under load
Front-end & render performance
Cuts render-blocking JavaScript, defers bundles, optimizes images, and fixes the layout shifts that hurt INP and CLS.
Pages that feel instant and interactive sooner
CDN, caching & edge delivery
Moves cacheable content to the edge and sets cache and compression policy correctly.
Faster global delivery, less origin load
Load testing & scalability
Models peak traffic, finds where the system breaks before customers do, and engineers the headroom.
The busiest day won't take the site down
As of June 2026 · revisit quarterly
What faster pages do to the business — the measured impact.
Independent industry findings — never Silicon Prime's own client results.
Speed converts. A study of 37 brands and 30M+ sessions found a 0.1-second mobile speed gain lifted retail conversion 8.4% and average order value 9.2%.
Slow loses visitors. As page load rises from 1 second to 3 seconds, the probability a visitor bounces increases by 32%.
Delay compounds. A 100ms delay can cut conversions 7%, and a two-second delay raises the bounce rate by 103% — the margin slowness erases.
A performance claim you can't see is one you shouldn't pay for. We baseline first and report the gain against your own numbers — before-and-after, on a dashboard that keeps running.
What's included
What performance optimization covers.
Slowness hides in layers, so the work spans the stack. Each item is a measured intervention, not a vibe.
Baseline & bottleneck diagnosis
We instrument real-user and synthetic monitoring, capture a baseline, and locate where time actually goes — front-end, API, code, or database — before changing a line. AI reads code and traces to surface anti-patterns a manual pass would miss.
Core Web Vitals optimization
We tune LCP, INP, and CLS against Google's thresholds using your real field data, not just a lab score — so the gain shows up for real users and in Search Console.
Database & query optimization
We profile the slow queries, add or correct indexes, eliminate N+1 patterns, and tune the access layer — the highest-leverage fixes on most enterprise apps, and the ones a rewrite never addresses.
API, caching & CDN delivery
We cut latency in service calls, set caching and compression policy correctly, and push cacheable content to the edge — faster responses and lower origin load and cloud cost together.
Load testing & scalability engineering
We model realistic peak traffic, find the breaking point, and engineer the headroom — connection pools, autoscaling, query concurrency — so the busy day is boring.
Measurement, monitoring & handover
We leave the monitoring and load-test harness in place, instrumented for regression, and train your team to read it — so performance is maintained, not re-bought next year.
What you get — all assigned to you
How it runs
Six steps, one measured loop.
The same delivery discipline behind our re-engineering work, focused on speed and scale — one accountable lead, no handoffs.
STEP 01
Baseline
Instrument real-user and synthetic monitoring; capture today's numbers and the targets we'll be judged against.
Output: a documented starting point
STEP 02
Profile
Put AI on the code, logs, and traces to find where time actually goes across the stack.
Output: a ranked bottleneck list
STEP 03
Diagnose
Confirm the root cause of each bottleneck, not the symptom.
Output: a fix plan ordered by impact-per-effort
STEP 04
Fix
Engineers implement the fixes — queries, indexes, render path, caching, API shape — inside your environment.
Output: the optimized changes
STEP 05
Load-test
Model peak traffic and prove the fix holds under it.
Output: a validated scalability ceiling
STEP 06
Verify
Re-measure against the baseline and report the before-and-after.
Output: the proven gain, monitoring left running
Straight talk
Twelve years of keeping one platform fast — without ever taking it offline.
The hardest version of performance optimization isn't a one-time speed-up; it's keeping an application fast across more than a decade of growth while it stays live the whole time. That's the work we've done on Bridge Athletic since 2012 — carrying a sports-tech platform through repeated re-platforming and performance optimization, paying down the debt that slows a system each pass, never going dark.
It grew into the platform now used by USC, the LA Rams, and MLB and MLS teams — the kind of load that punishes a slow application, sustained for 12+ years. The same discipline holds BJ's Restaurants at twice-a-week releases with zero critical defects across four years.
We baseline first and report the numbers, because a performance claim you can't see is one you shouldn't pay for.
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 optimize it with us.
We find it before we fix it. AI reads your code, logs, and traces to locate the real bottleneck; our engineers fix it. No rewrite-by-reflex, no guessing — measured diagnosis, targeted fix.
Proven before and after. We baseline first and report the gain against your own metrics. A result you can't see on a dashboard isn't a result.
Built to stay fast. We leave the monitoring and load-test harness in your hands and train your team — so the gain holds instead of decaying back to slow.
Founder-led, built to transfer. One accountable lead answers for the numbers — and the optimized system, the harness, and the findings are assigned to you under full work-for-hire IP.
Where it lands first
Where optimization moves the needle most.
Ecommerce
Where every 100ms maps directly to conversion and basket size; we tune Core Web Vitals and checkout latency against live catalog and order load.
Ecommerce software →High-traffic SaaS
Dashboards and APIs that must stay fast as customers and data grow; query tuning and scalability engineering carry the load.
Software re-engineering →Long-lived enterprise platforms
Applications a decade into production where accumulated technical debt has quietly throttled speed; we pay it down without downtime.
Application modernization →Questions buyers ask before they optimize.
Thirty minutes · no pitch deck
Tell us where it drags — we'll prove the fix in numbers.
Bring the slow page, the timeout, or the traffic spike you're dreading. We'll show how we'd baseline it, put AI on the code and logs to find the real bottleneck, and give you a measured path to an application that holds up under load.