Service · Cloud
Backends that scale to zero and bill only when they run.
An event arrives, code fires, work gets done, and the bill stops the moment it goes idle. No fleet to patch, no capacity to guess. We build it in your own cloud — AWS, Azure, or Google Cloud — and when serverless is the wrong tool, we'll tell you.
Event-driven · scales to zero
TRIGGERS
MANAGED STATE
The real problem
Why pay for servers that sit idle most of the day?
Most backends are sized for their busiest minute and billed for every minute they aren't. A fleet provisioned for the lunch rush or Black Friday runs — and bills — flat through the 3 a.m. lull, while someone still patches the OS and gets paged when a node falls over.
Serverless inverts that: you write the function, the platform runs and scales it on demand, and you pay per execution — to zero when nothing is happening. The catch is that this only pays off for the right shape of workload. Getting the fit right is the entire engineering problem.
The bill when nothing runs — the platform scales your functions on demand, and you pay per execution instead of for an idle fleet.
Scale-to-zero · the core mechanism
Of AWS customers already run on Lambda — serverless is mainstream backend, not an experiment.
Where it pays off
Where serverless actually earns its place — and what each pattern delivers.
It's a model that pays off in specific workload shapes: bursty, event-driven, or idle-heavy work where paying per execution beats an idle fleet. (Examples are illustrative, not client results.)
Spiky, event-driven APIs & backends
Functions behind a gateway, scaling instantly from zero to a flood and back. Absorb spikes, pay nothing idle.
A campaign API idle for weeks then taking 50,000 hits in an hour scales up and bills only for that hour — not a cluster sized for a twice-a-year peak.
Stream & file processing pipelines
A function fires on every new record, upload, or message, fanning out to thousands of parallel runs when volume surges. Throughput scales with the data.
A document upload triggers a function that makes the thumbnail and extracts the text in seconds — a thousand at once in a busy hour, nothing overnight.
Scheduled jobs & IT automation
Replaces always-on cron boxes with functions that fire on a schedule or event — backups, reports, provisioning, cleanup. Routine ops, no server to maintain.
A nightly reconciliation that needed a dedicated VM now runs as a scheduled function for cents a month; a provisioning task that took hours runs in minutes.
Webhook & integration handlers
Receives webhooks from third-party systems and routes, transforms, or acts on them through functions wired to your systems of record. Stand up fast, scale on their own.
A payment webhook fires a function that updates the order and notifies fulfillment instantly — an endpoint that costs nothing between events and absorbs a launch-day surge.
Real-time notifications & fan-out
Reacts to an event — an order, a status change, a threshold breach — and fans out notifications and downstream actions in parallel. Immediate, scales with volume.
An inventory threshold trips and a function alerts the buyer, updates the storefront, and opens a reorder at once — only when it's actually hit.
Managed backends for web & mobile
Assembles a backend from managed building blocks — functions, database, object storage, hosted auth — so a product ships with no server tier. Faster launch, lower ops load.
A new mobile app launches on a serverless backend that scales with sign-ups from day one — the team ships the product instead of hardening servers first.
Vendor-published & independent findings · revisit quarterly
What serverless does to those processes — the measured impact.
Independent and vendor-published findings on the technology, cited as third-party evidence — never Silicon Prime's own client results.
Event-driven data processing. Cost reduction at FINRA, running half a trillion validations across 37 billion market events daily on AWS Lambda.
IT automation. Autodesk cost savings on account provisioning (factoring labor), cutting it from 10 hours to 10 minutes with Lambda.
Scale-to-zero elasticity. Toyota Connected scaled to 18× usual traffic (18B transactions/month) and cut aggregation jobs to 1/40th of 15+ hours, paying only for what it consumed.
Serverless pays when work is bursty — and costs more at sustained throughput. So we model per-invocation cost against an always-on baseline before we build, and document the crossover where a container wins.
What's included
What serverless application development covers.
The scope below is the difference between serverless that's cheap and fast and a function sprawl that's slower and more expensive than the server it replaced.
Fit assessment & workload shaping
We decide what actually belongs on serverless — bursty, idle-heavy work fits; sustained high-throughput and sub-10ms floors usually don't. We model per-invocation cost against an always-on baseline, with the honest "don't make this serverless" call included.
Event-driven architecture & FaaS design
We design the event flow — sources, the functions that react, and the managed services that hold state — so the system is loosely coupled and each piece scales on its own. Functions stay stateless; state lives in managed stores.
Managed backends & integration (BaaS)
We assemble the backend from managed building blocks — functions plus a managed database, object storage, hosted auth, queues, and event buses — wired through your access controls, with no server tier to provision or patch.
Cold-start, performance & cost engineering
We engineer the parts that bite: cold-start latency (provisioned concurrency, runtime and memory tuning), concurrency limits, and the per-invocation cost model — so the system meets both its latency and cost targets, crossover point known.
Security, IAM & observability
Each function runs under least-privilege, scoped permissions; secrets are managed, not embedded; and the event flow is instrumented with distributed tracing so a request is followable across functions and services.
Infrastructure-as-code & enablement
The entire application is defined as code (SAM, Serverless Framework, Terraform, or CDK) so it's reproducible and reviewable, ships behind a staged rollout, and your team is trained to deploy functions and read the traces and cost dashboards.
What you get — all assigned to you under full work-for-hire IP transfer
How it runs
How a serverless engagement runs.
The same delivery model behind all our engineering work, tuned for serverless — one accountable lead, fixed scope, no handoffs.
STEP 01
Assess
Map the workloads, model per-invocation cost against an always-on baseline, and decide what belongs on functions and what doesn't.
Output: a fit verdict, target architecture & metrics
STEP 02
Design
Design the event flow, the functions, the managed-service backing, and the cold-start and concurrency strategy — reviewable before code.
Output: an architecture & a cost model with the crossover
STEP 03
Build
Develop the functions and wire the event sources and managed services in your own cloud account, defined entirely as IaC, with scoped IAM and tracing in place.
Output: a working app behind your access controls
STEP 04
Operate & enable
Staged rollout, then production, with per-function cost and cold-start latency watched against kickoff targets, and your team trained to deploy and extend it.
Output: a production system & a team that owns it
Straight talk
The record behind a system you put real load on.
We won't claim a serverless case study we don't have — so here is the genuinely relevant record, labeled for what it is. The closest fit is an event-and-integration-heavy marketplace backend — the exact workload pattern serverless exists to carry, even though we built it before serverless was the default.
We'll tell you plainly when a workload doesn't belong on serverless — which a firm paid by the function won't.
Silicon Prime is a Stanford-rooted Responsible AI and engineering lab, founded 2011, run by founder Kelvin Tran — 20+ years of production engineering, personally accountable for every engagement.
The public record
The relevant record — labeled for what it is.
Closest fit · event-driven at scale
YardClub
A contractor-to-contractor equipment marketplace we built end to end — listings, payments, and the transaction infrastructure underneath. An event-and-integration-heavy backend, exactly the workload pattern serverless is built for. Processed $120M+ and was acquired by Caterpillar in 2017. Built before serverless was the default — cited for the architecture pattern, not as a from-scratch serverless engagement.
TechCrunch ↗Why build serverless with us.
We tell you when serverless is the wrong answer. The expensive mistake is forcing a sustained, high-throughput workload onto functions and paying more for worse latency. A container or managed instance is a recommendation we'll make and defend, not a fee we avoid.
Cost and cold-start engineered, not assumed. We model the per-invocation economics and cold-start latency before building and document the crossover where always-on wins — so the bill and the latency are forecasts you've already seen.
Founder-led, one accountable lead. No account managers, no handoffs — the engineer who designs the architecture answers for how it runs in production.
Built to transfer, whole-stack in-house. Functions, IaC, the cost model, and code are assigned to you under full work-for-hire IP, and your team is trained to run them. Because serverless sits on a cloud foundation and needs a secure delivery path, we run all of it — so the system isn't stranded between vendors.
Where it lands first
Where serverless earns its keep first.
Fintech
Event-driven transaction processing, real-time fraud and decisioning, and webhook handling where work is bursty and every event needs a scoped, auditable function.
Fintech software →Ecommerce & retail
Storefront APIs and order pipelines that scale to zero off-peak and absorb peak-day spikes without a pre-sized fleet, plus stream processing for catalog, pricing, and inventory events.
Ecommerce software →SaaS & startups
Managed serverless backends that let a new product launch and scale with sign-ups from day one, with no backend fleet to provision or patch.
SaaS development →Questions buyers ask before they build.
Thirty minutes · no pitch deck
Ready to stop paying for idle servers — where that makes sense?
Bring the workload and the bill it's running up. We'll tell you honestly which pieces belong on serverless, which belong on something always-on, what it takes to build, and what it costs to run.