epicX helps fintech startups and growth-stage firms hire fintech developers with proven industry expertise. Our pre‑vetted financial development talent helps you build secure, compliant, and scalable fintech software solutions built for speed, trust, and regulatory alignment.
"It was the fastest we've ever hired vetted devs. And the quality? Outstanding."
"We were drowning in tech debt. epicX plugged in senior devs fast. Absolute lifesavers."
"We scaled our engineering team by 3x without touching recruitment or burning budget."
"We’ve worked with fancy agencies before. This felt different. Just pure focus and execution."
"It was the fastest we've ever hired vetted devs. And the quality? Outstanding."
"We were drowning in tech debt. epicX plugged in senior devs fast. Absolute lifesavers."
"We scaled our engineering team by 3x without touching recruitment or burning budget."
"We’ve worked with fancy agencies before. This felt different. Just pure focus and execution."
"It was the fastest we've ever hired vetted devs. And the quality? Outstanding."
"We were drowning in tech debt. epicX plugged in senior devs fast. Absolute lifesavers."
"We scaled our engineering team by 3x without touching recruitment or burning budget."
"We’ve worked with fancy agencies before. This felt different. Just pure focus and execution."
"Everything was perfect. No hand-holding, no surprises. Just people who know what they’re doing."
"No fluff, no waiting. Just solid engineers who got stuff done from week one."
"Never knew hiring could be this calm and predictable. Such a relief for our product team."
"Highly recommend them as a no-bullshit partner for anyone trying to scale engineering without chaos."
"Everything was perfect. No hand-holding, no surprises. Just people who know what they’re doing."
"No fluff, no waiting. Just solid engineers who got stuff done from week one."
"Never knew hiring could be this calm and predictable. Such a relief for our product team."
"Highly recommend them as a no-bullshit partner for anyone trying to scale engineering without chaos."
"Everything was perfect. No hand-holding, no surprises. Just people who know what they’re doing."
"No fluff, no waiting. Just solid engineers who got stuff done from week one."
"Never knew hiring could be this calm and predictable. Such a relief for our product team."
"Highly recommend them as a no-bullshit partner for anyone trying to scale engineering without chaos."
Building fintech products is not just about code; it’s about trust, compliance, and delivering seamless financial experiences. epicX connects you with fintech developers who speak the language of finance and build with regulatory precision.
4+ Years of Experience with Fintech Solutions
Product-First Mindset for Every Financial Platform
Advanced Capabilities in AI, Blockchain, and Data Analytics
Deep Expertise in Finance, Security, and Compliance
Every fintech product is different. Whether you're building a digital bank, modernizing your legacy systems, or optimizing payments infrastructure, we match you with fintech developers who get your use case, ask the right questions, and move fast, without cutting corners.
Our engineers are skilled at integrating reliable, multi-currency, and PCI-compliant payment systems that power seamless transactions.
epicX helps fintech startups skip hiring friction and get product-ready engineers who understand financial systems, compliance, and secure infrastructure, right from the start.
At epicX, we specialize in connecting startups and financial companies with engineers who understand the complexity of building in fintech. Here’s what our clients typically achieve:
Save 25% on development costs by avoiding recruitment fees, onboarding delays, and bad technical hires
Speed up transaction performance by 40% through optimized architecture and backend infrastructure
Launch new products 30% faster with agile fintech teams who are ready to contribute from day one
Looking to hire fintech software developers who understand banking systems, compliance, and modern payment infrastructure? epicX gives you a direct line to pre-vetted fintech engineers, ready to build from day one.
From digital wallets to lending apps, our engineers have shipped fintech products that meet banking standards and user expectations.
We only place dedicated fintech software engineers, directly managed by you. No layers, no delays, no surprises.
AML, KYC, PCI DSS, SOC2 — we bring pre-vetted fintech engineers who know the rules and code to meet them.
Launch faster with fintech-savvy developers who reduce build time without compromising security or performance.
Work directly with your remote team, backed by local support from epicX to handle logistics and scaling.
Try your dedicated software developer before committing. Only continue if you're confident they can deliver for your fintech roadmap.
Whether you're a startup validating an MVP or an enterprise scaling infrastructure, epicX matches your growth with flexible team sizes and seniority levels.
Access top fintech engineers from around the world — handpicked to overlap with your working hours for seamless collaboration and faster iteration.
SaaS is still the golden child of tech in 2025.
Everywhere you look, another startup is launching a product that runs in the browser, charges a subscription, and scales like wildfire.
But building one isn’t cheap. The cost can swing wildly depending on the idea, the complexity, and the team behind it.
Think of SaaS like opening a digital factory. You’re not producing hardware, but you’re building a system that people rely on every day.
Once it’s up, it can scale globally without adding more factories, workers, or raw materials. That’s why investors, especially accelerators like Y Combinator, keep betting on SaaS-heavy portfolios.
If SaaS looks like the fastest route to scalable revenue, then the real question every founder asks is the same: how much does it actually cost to build one?
This write-up is all about answering it.
After the AI boom, SaaS has become the business model everyone is chasing. Service-based models that rely on billable hours or manual labor are losing ground.
For example, instead of paying a legal consultant by the hour, businesses now subscribe to legal SaaS tools like Ironclad that automate contracts.
Instead of hiring a marketing agency, they turn to platforms like Jasper that generate copy in seconds. The shift is clear — people want scalable, always-available software over unpredictable service work.
Wrapping AI into SaaS models is also the fastest way to monetize new technology.
Take Runway: instead of selling a one-off AI model for video editing, they packaged it as a subscription tool that any creator can use in the cloud.
ElevenLabs did the same with AI voice synthesis, turning complex model training into a browser-based product with tiers starting at $5 a month. That move from raw AI models to SaaS platforms is where the money flows, because it creates recurring revenue and keeps customers locked into ecosystems.
According to Gartner, the SaaS market is expected to pass $300 billion by 2026, and AI-driven platforms are leading the charge.
The formula is proven: pick a niche, solve it with SaaS, monetize through subscription. That’s why founders everywhere are rushing in.
The momentum has companies racing to productize services, package expertise, and capture recurring dollars.
The feature set drives the largest cost difference. A lightweight SaaS with login, dashboard, and billing can be built cheaply using modern AI coding tools and boilerplates.
But if you want your app to behave like Notion with real-time collaboration, it will cost more than a simple SaaS like Buffer that only schedules posts.
A generic UI kit can save money, but polished SaaS design is what attracts and retains users. If you’re building an enterprise-facing tool where teams spend hours daily, UX quality matters.
Think about the difference between a barebones CRM and the clean usability of HubSpot. The latter requires more design investment.
The cost also depends on whether your SaaS needs third-party integrations, APIs, or a custom backend.
A payment-enabled SaaS using Stripe or Braintree requires extra engineering hours compared to a standalone SaaS with no external dependencies.
Similarly, adding AI features like ChatGPT-style assistants adds cost upfront but makes your platform more competitive.
Hiring developers in North America costs significantly more than working with teams in regions like Eastern Europe or Pakistan.
With AI-assisted coding, lean teams can now deliver in weeks what once required large engineering groups. That’s why today, a quality MVP can be built by a 2–3 person team without crossing six figures.
If your SaaS deals with healthcare, finance, or enterprise clients, compliance adds extra development cycles. HIPAA, GDPR, or SOC 2 readiness all increase costs.
For example, a scheduling app like Calendly is cheaper to launch than a fintech SaaS requiring encrypted transactions and audit logs.
Cloud hosting, storage, and scaling are ongoing costs, but building for scale from day one adds to upfront costs.
A small MVP might run fine on shared cloud services, but if you want Zoom-level scaling, you’ll invest more in architecture, load balancing, and server redundancy.
Several levers pull the final price. Understand these and you control the bill.
Every added module increases scope. Basic authentication and dashboards are one thing, but once you add billing, team roles, analytics dashboards, or third-party integrations (Slack, Salesforce, HubSpot), engineering time multiplies.
A startup aiming for something as broad as Notion will naturally pay far more than a company building a lightweight CRM like Pipedrive.
If you target healthcare, finance, or education, expect extra costs.
Encryption at rest, penetration testing, logging frameworks, and legal reviews come into play. Achieving SOC 2 or HIPAA compliance is not a weekend project.
For example, a health records SaaS handling patient data might see compliance work adding six figures to the overall bill.
Onshore engineers in the US or Europe can cost $120–200 per hour. Offshore engineers in Pakistan or Eastern Europe may charge $30–60 per hour.
Remote teams save burn, but they require strong product leadership and overlap hours. Platforms like epicX strike a balance with vetted global engineers who already know SaaS patterns.
The faster you want to ship, the bigger your burn. Compressing timelines means hiring larger teams, running parallel sprints, and pushing overtime.
For example, a founder who wants a product live before a major conference might pay 1.5x more than a team spreading the same build over six months.
Cloud costs scale with ambition. Hosting a standard dashboard app with Postgres is cheap.
Hosting an AI-driven transcription tool like Otter.ai means GPU servers, LLM inference, and high data storage; bills jump quickly.
A startup doing media streaming will also see CDN and bandwidth costs dominate early budgets.
SaaS is not just about charging a flat monthly fee anymore.
As markets mature and AI reshapes customer expectations, platforms are experimenting with models that maximize revenue while keeping acquisition costs low. Here are the most common ones shaping 2025.
Still the backbone of SaaS, subscription pricing provides predictable recurring revenue. Customers pay monthly or annually for access, often with discounts for longer commitments.
Tools like Grammarly and Figma thrive here because users see daily value. This model works best when the platform becomes an essential workflow.
Freemium lowers barriers to entry by offering a free plan with basic features, nudging users to upgrade as they grow.
For example, Canva gives away most design tools but charges for brand kits, premium templates, and team collaboration. This model is effective in competitive markets where user adoption is the key growth lever.
Also called pay-as-you-go, this model scales costs with customer usage. It’s popular in infrastructure and API-driven SaaS like Twilio or OpenAI, where charging per request or data processed makes sense.
With AI adoption, more startups are shifting to usage-based pricing to align customer cost with actual value delivered.
Tiered pricing allows segmentation by company size, offering starter, growth, and enterprise packages. This lets SaaS platforms capture value from both small businesses and large enterprises.
HubSpot exemplifies this, with clear progression in price and features as teams expand.
In 2025, many SaaS companies are blending models. An AI SaaS might combine freemium onboarding with usage-based billing for advanced features.
Others experiment with outcome-based pricing, charging customers only when results are delivered, especially in sales automation or ad optimization SaaS.
Other models like transactional SaaS (charging per transaction, common in fintech) and marketplace SaaS (where SaaS enables a two-sided marketplace and takes a cut) are also in demand, but subscription, freemium, usage, and tiered remain the most widely used today.
You don’t need to reinvent every layer. The key is standing on shoulders instead of building plumbing yourself.
Here are the main strategies.
Community-driven SaaS boilerplates like Bullet Train, Nodewood, or Laravel Spark come with core features like login, subscriptions, and admin dashboards pre-built.
That cuts months of development. For an MVP, this might mean launching in two months instead of six.
Quick Scenario: if you want a project management SaaS, a boilerplate already covers user auth, so your team only focuses on task workflows.
Modern SaaS rarely builds everything from scratch. Stripe powers billing, Auth0 or Supabase handle authentication, SendGrid runs email, and headless CMS tools like Strapi or Sanity manage content.
These reduce custom code and speed up compliance, since vendors already invest in security. Scenario: instead of building your own payment gateway, Stripe lets you go live in days.
By building with small, replaceable services, you avoid future rewrites.
For example, you could start with OpenAI APIs for AI features and later swap them for a fine-tuned in-house model. This keeps early costs down while leaving room to upgrade.
The fastest-growing SaaS often began narrowly. Calendly started with scheduling links before adding teams and integrations.
By limiting scope, you shorten timelines and clarify product-market fit. Later, you can expand horizontally into more use cases.
Building a SaaS platform requires a small, focused crew plus a handful of specialist roles for scale and compliance. The exact mix changes with product scope. If the goal is a simple scheduling tool, the team remains small.
If the target is a real-time collaboration product or an AI assistant, more senior engineers, a DevOps lead, and a data scientist become essential.
Below are practical roles, why each matters, and how they map to real examples.
Owns the roadmap, tradeoffs, and feature prioritization. For a product like Calendly, this role defines scheduling flows, integrations, and conversion points. Without strong product leadership, teams build features that users do not want.
Designs flows, reduces friction, and raises conversion. A polished UI is what separates a one-off tool from a sticky SaaS product. If the goal is a Notion-like interface, the design investment is higher than for a single-purpose admin dashboard.
Builds the client layer, state management, and interactive UX. Real-time features greatly increase frontend complexity. For example, a collaboration app with shared cursors needs extra engineering and testing compared with a static dashboard.
Implements business logic, multi-tenant models, databases, and integrations. A multi-tenant architecture for enterprise customers requires careful isolation of data and tenants, increasing development time over a single-tenant MVP.
Keeps releases stable through test plans, automation, and regression testing. For apps with frequent releases, QA reduces expensive rollbacks and production incidents.
Manages CI CD, deployments, monitoring, and cost control. Cloud cost surprises are common. Experienced DevOps saves money by choosing the right instance types, autoscaling policies, and backup strategies.
Necessary when handling regulated data or enterprise clients. For HIPAA or SOC 2 readiness, this role guides encryption, logging, audits, and policies.
Typical onboarding cadence and ramp
Tech stack examples that map to budget and speed
Budget template quick view
Launching a product is the start of continuous spend. Plan for predictable recurring lines and a surprise buffer. Ongoing costs are where many SaaS runs out of runway.
Below are the main categories, realistic examples, and a compact monthly scenario table to help forecast.
Cloud bills rise with traffic, data volumes, and compute intensity. A simple B2B app might pay $500 to $2,000 per month on cloud resources and managed databases.
An AI-powered product that runs inference regularly or a media-heavy app can see monthly bills jump to $10,000 to $50,000 or more, especially when using GPU instances.
Example: running LLM inference even at modest scale can cost thousands per month; datasets and backup storage add to the bill.
External services carry variable fees. Stripe takes a cut on payments. Twilio bills per message or call. LLM providers bill per token or request.
For AI-first apps, API or inference spend often becomes the single largest monthly line item.
Example: a chatbot used by 10,000 monthly active users with moderate token use can incur monthly inference costs in the low five figures.
Monitoring tools, alerting, SRE hours, and incident response all cost money. Tools like Datadog, Sentry, and PagerDuty add predictable subscription lines. Budget for on-call rotations or outsourced SRE to avoid long outages that cost customers and revenue.
Support staff cost scales with user base and ticket volume. Early-stage SaaS may start with outsourced support or one support engineer, then invest in dedicated onboarding specialists as ARR grows.
Example: one support engineer can handle early growth, but at 1,000+ seats a team will be needed for quick SLAs.
Expect to spend on feature work, bug fixes, and technical debt cleanup. A conservative rule: allocate 20 to 30 percent of initial build cost annually to maintenance and incremental improvements.
For AI-heavy workloads, plan higher. For example, an initial build of $100k suggests $20k to $30k per year for maintenance. If models or inference are central, the maintenance percentage could rise to 40 percent.
For regulated verticals, recurring audit and compliance costs matter. Annual SOC 2 audits, penetration testing, and compliance tooling can add thousands to tens of thousands per year.
Set aside 20 to 30 percent of the initial build cost as annual maintenance for typical SaaS. If the product is AI-intensive, budget closer to 30 to 50 percent of build cost annually because inference and data pipelines are expensive to maintain.
epicX is not just another outsourcing vendor. It’s a London-based tech partner with delivery offices in Pakistan and South Africa, built around one promise: faster access to elite engineers without the usual risks of remote hiring.
Unlike freelancer platforms or staffing agencies, epicX delivers full-time, culture-fit developers who are pre-vetted, supervised, and available to start within 48 hours.
That speed is backed by transparency, no proxies, no moonlighters, no middle layers. Just engineers who plug directly into your codebase, tools, and team.
What makes the cost model compelling is the balance between quality and savings.
A mid-level US engineer costs $10K–12K per month. The same caliber talent through epicX costs around $5K, with the added benefit of on-ground oversight and a 14-day risk-free trial.
At epicX the focus is on:
In short, epicX gives startups predictable milestones, faster delivery, and up to 65 percent cost savings compared to onshore hiring.
SaaS is tempting, but founders often burn through budgets faster than expected. Studies suggest more than 90 percent of SaaS startups fail before hitting Series A, and cost mismanagement is one of the top reasons.
It’s easy to fall into the trap of chasing every feature at once. An MVP for a project management tool doesn’t need real-time AI copilots, custom dashboards, and integrations with 20 services.
Those add months of work. Think of how Basecamp started —> simple task lists, no frills —> before expanding.
Switching frameworks midway is another common disaster. A team that builds in Vue then shifts to React because “investors prefer it” ends up redoing half the codebase. Every rewrite eats time, trust, and cash.
Some teams launch with a shaky deployment pipeline and no monitoring. That’s fine with 20 users, but once a customer demo crashes, the firefighting costs add up. SaaS giants like Slack built reliability into their DNA early, which is why they scaled smoothly.
Healthcare, finance, or education apps cannot skip security. SOC2 audits, HIPAA readiness, and GDPR compliance are not “nice to haves.” They demand time, consultants, and often code refactors. Leaving this late usually doubles the cost.
These pitfalls don’t just hurt budgets; they crush morale. Teams that overspend or rebuild repeatedly often lose their runway before finding product-market fit.
SaaS in 2025 is both a gold rush and a minefield. The gulf between a $50K MVP and a $500K enterprise-ready build isn’t just about scale. It’s about security, infrastructure, compliance, and speed to market.
The key is clarity: know your MVP scope, plan for recurring costs, and avoid the mistakes that derail most founders. SaaS is not cheap, but with the right strategy it becomes one of the most capital-efficient business models in tech.
So here’s the real question: will you burn your budget chasing the wrong things, or map a cost plan that lets you build, launch, and grow with confidence?
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