Do you only work with funded SaaS startups?

No. We work with funded startups, bootstrapped founders, and product teams inside larger companies. Funded SaaS is where we have the most case studies, but the engineering process is the same.

What does a typical week with your team look like?

Two-week sprints, async-first communication on Slack or Teams, planning at the start of each sprint, and a working demo at the end. Code lands in your repos, in your CI, behind your code review. You see progress every day, not in monthly status decks.

Can you take over a SaaS project from another team?

Yes — and a meaningful share of our work starts this way. We do a code and architecture audit first, document what we find, and propose a path forward. Sometimes that's stabilising and continuing. Sometimes it's a focused rewrite of one or two modules. We are direct about what makes sense.

Will you sign an NDA before we share the product details?

Yes. We sign NDAs before discovery calls when requested.

Who owns the code and the IP?

You do. All source code, design assets, infrastructure accounts, and third-party integrations are owned by your company. We deliver into your repositories, your cloud accounts, and your domain. We do not retain reusable rights to your product code.

Can you build the billing, subscriptions, and metering layer?

Yes. We build Stripe-based billing including plans, free trials, proration, usage-based metering, invoice generation, dunning flows, and admin override. We have implemented this across multiple SaaS products and reuse a battle-tested pattern.

How do you handle multi-tenancy?

Default is shared schema with row-level isolation enforced in the data layer and at the API boundary. We move to schema-per-tenant or database-per-tenant when the product genuinely requires it — usually for compliance reasons. We make this call early and document it.

Can you embed AI features inside the SaaS product?

Yes. We integrate OpenAI, Anthropic, and open-source models into product workflows — copilots, search, summarisation, document processing, recommendations. We design fallbacks for when the model is wrong, slow, or unavailable, because production AI without guardrails breaks user trust quickly.

Do you support the product after launch?

Yes. Most clients continue with us on a maintenance and feature-development retainer after launch. Bug fixes, performance work, new modules, and ongoing iteration. The team that built it is the team that maintains it.

How do you handle scope changes mid-build?

Scope changes are normal in SaaS. We re-baseline at sprint boundaries, not mid-sprint. Each change has a clear cost in time and money before it lands in the plan. No surprise invoices.

SaaS Web App Development for Startups

■ Who this is for

A good fit if you're building real SaaS

Funded SaaS founders building V1 or scaling toward Series A
Self-funded founders with a working prototype that needs to ship
Product teams that need senior engineering capacity without hiring
Companies migrating from no-code or AI-built prototypes to a real codebase
Existing SaaS products that need a rebuild or major architecture overhaul

■ Probably not a fit

We'll be honest if it's the wrong call

Pre-idea founders looking for a technical co-founder
Projects that only need a marketing site or landing page
Engagements that need a single hourly contributor
Teams looking purely for the cheapest possible bid

Featured client

Case Study · IPL Franchise · Internal Analytics SaaS

Leading Edge

Internal platform built

BigQuery

Backend data warehouse

Stack

React · Next.js · Node.js · BigQuery · Python

■ Real work · Featured engagement

We built Leading Edge — the internal analytics platform that powers Rajasthan Royals

Rajasthan Royals — one of the founding IPL franchises and the inaugural T20 champions — partnered with Appycodes to build their internal analytics SaaS platform, Leading Edge. The platform powers the decisions the cricketing operations team makes day to day: player scouting across the global player pool, the trade engine for IPL auction modelling, ongoing player analytics for every athlete on the roster, and projection models that feed match strategy.

The data warehouse sits on Google BigQuery — every ball bowled across every competitive match the system tracks, ingested and structured. Most of the engineering challenge was not the front-end. It was the queries. Player scouting against multi-season ball-by-ball data, with strike-rate-against bowler-type filters, situational match-state segments, and venue-specific performance windows, runs across hundreds of millions of rows. Naive SQL costs minutes per query — unusable for an interactive scouting interface.

Case Study · B2B Marketplace

$5M+

Funded by Fuel Ventures

800K+

Orders processed

Stack

React · Node.js · PHP · PostgreSQL

■ Real work

How we helped CREOATE process 800,000+ orders

CREOATE raised $5M from Fuel Ventures to build a B2B marketplace connecting independent retailers with global suppliers. The product needed to handle two distinct user journeys at the same time — buyers browsing thousands of SKUs, and suppliers managing inventory, orders, and payouts — without either side feeling slow.

Our engineering team contributed across the React frontend, the Node.js services that power search and checkout, and the PHP layer that handles supplier-side order management. The hard part was not any single feature — it was keeping the marketplace responsive as catalog size, order volume, and supplier count grew in parallel.

■ Stack we'd pick today

An opinionated SaaS stack — and why

We are not stack agnostic. After building dozens of SaaS products, we have strong opinions about what is worth your time and what creates pain at month nine. Here's what we reach for by default. We deviate when there's a real reason — not because something is trending.

Frontend — Next.js (App Router)

Real server rendering, real routing, real image and font handling. We pick Next over Remix because the ecosystem and hiring pool is deeper, and because most SaaS frontends benefit more from incremental static rendering than from Remix's loader model.

Backend — Node.js (Fastify) or Laravel

Node + Fastify when the product is API-heavy and needs websockets or AI streaming. Laravel when the surface area is large CRUD, admin, and the team wants batteries-included. We avoid microservices until you genuinely need them — usually never for the first two years.

Database — PostgreSQL

Default for almost every SaaS. ACID transactions, JSON columns when you need flexibility, full-text search good enough for most products, and a clear path to read replicas when you scale. We use Mongo only when the data is genuinely document-shaped.

Auth — Clerk or custom JWT + sessions

Clerk if you want SSO, magic links, and org/team support without building it. Custom auth when you need full control over the session model — usually for products with strict tenancy or compliance needs.

Billing — Stripe

Plans, free trials, proration, usage-based metering, dunning. We have a reusable billing pattern that handles edge cases like mid-cycle plan changes, failed cards, and grandfathered pricing. Not glamorous — billing bugs lose customers fast.

Hosting — Vercel + AWS or DigitalOcean

Vercel for the frontend. AWS or DigitalOcean for the backend, database, queues, and storage. We avoid lifting and shifting onto any single PaaS that locks you in. Boring infrastructure ages well.

■ Real work

100+ shipping calculators inside Easyship

Easyship is a global shipping platform now valued at over $40M, helping merchants compare and book carriers across two hundred countries. The product runs on a deceptively complex set of calculators — every quote requires reconciling rate cards, customs rules, surcharges, and merchant-specific contracts in real time.

We built and maintained many of these calculator engines in Vue, React and TypeScript, with Node services backing them. The interesting engineering was not the math — it was keeping the rules engine testable across all geographic and language combinations.

Case Study · Shipping SaaS

$40M+

Company valuation

100+

Calculators shipped

Stack

React · TypeScript · Node.js · Vue.js

■ How we work

From kickoff to live SaaS, in six steps

01

Discovery sprint

One week. We map the product, users, business model, and the hard problems hiding under the surface. Output: a written architecture and a concrete plan for the first 90 days.

02

Architecture and stack lock

We choose the stack, design the data model, and define the multi-tenancy approach before writing production code. Decisions get documented so the next engineer to join is not confused.

03

Sprint zero

Auth, billing scaffolding, base UI system, CI/CD, and a deployable shell. By the end of sprint zero you have something a real human can log into.

04

Feature sprints

Two-week sprints. Planning, build, demo, ship. You see progress every Friday. Scope changes get re-baselined at sprint boundaries, not mid-sprint.

05

Pre-launch hardening

Performance pass, security review, load test against the realistic peak, error reporting and analytics wired up. Launch with monitoring already running.

06

Launch and 30-day stability watch

We stay on full availability for the first month after launch. Real users find real bugs. Then we move into the standard maintenance and feature retainer if you want us to keep going.

■ Honest comparison

Appycodes vs your other options

	Freelancer	Local agency	In-house hire	Appycodes
Senior engineers	Maybe	Mixed	Yes — once hired	Yes
Time to start	1-2 weeks	2-4 weeks	6-12 weeks	1-2 weeks
Continuity if someone leaves	High risk	Medium	Yes	Built in
Familiar with funded SaaS context	Rare	Sometimes	If you hire well	Yes
Owns code and IP	Mixed	Yes	Yes	Yes — fully
Bug response after launch	When available	Business hours	Yes	Yes
Operational overhead for you	Low	Medium	Highest	Low

Senior engineers

FreelancerMaybe
Local agencyMixed
In-house hireYes — once hired
AppycodesYes

Time to start

Freelancer1-2 weeks
Local agency2-4 weeks
In-house hire6-12 weeks
Appycodes1-2 weeks

Continuity if someone leaves

FreelancerHigh risk
Local agencyMedium
In-house hireYes
AppycodesBuilt in

Familiar with funded SaaS context

FreelancerRare
Local agencySometimes
In-house hireIf you hire well
AppycodesYes

Owns code and IP

FreelancerMixed
Local agencyYes
In-house hireYes
AppycodesYes — fully

Bug response after launch

FreelancerWhen available
Local agencyBusiness hours
In-house hireYes
AppycodesYes

Operational overhead for you

FreelancerLow
Local agencyMedium
In-house hireHighest
AppycodesLow

None of these options is universally right. Freelancers work for narrow, short tasks. In-house hiring is the right move when you have time and certainty. We tend to be the right call when you need senior delivery quickly, with continuity, without the overhead of an in-house team.

■ Questions we get

Real questions from real founders

If yours is not here, ask us directly.

About the author

Ritesh — Founding Partner, Appycodes

Ritesh leads engineering at Appycodes and has spent the last decade shipping SaaS products for funded startups across the UK, US, India and Australia — including CREOATE, Easyship, Khatabook, and others. His focus is on production engineering: the unglamorous decisions that keep a SaaS product fast, reliable, and easy to change six months after launch.

■ Other services