How We Work: Our Development Process

You’re about to hand a team your budget and your timeline, and trust them with whatever your product is supposed to become. That’s not a small thing. So before we talk about what we build, let’s talk about how, because the process is where projects either ship or quietly fall apart.

We’ve been doing this for 12 years across 250+ projects. The 98% on-time delivery rate and 95% client retention aren’t luck. They come from a process we’ve broken, fixed, and rebuilt enough times to know which parts actually hold up.

Here’s how it works.

Phase 1: Discovery (1-2 Weeks)

Every project starts with us listening. We don’t open with a sales pitch or hand you a feature checklist. We have actual conversations about what you’re trying to do, who’s going to use the thing, and what “shipped successfully” looks like in numbers.

What happens during Discovery

Stakeholder interviews. We talk to everyone who’ll feel the impact: founders, PMs, end users when we can get to them, the department heads whose teams have to actually adopt the thing. Skip this and you pay for it later. Half the projects we’ve inherited that went sideways traced back to a stakeholder nobody had spoken to. Thirty minutes with the right person beats two months of building in the wrong direction.

Technical audit. If you have existing systems, we dig in. What’s your current stack? Where are the bottlenecks? What integrations have to happen? We’ve inherited enough legacy codebases (Laravel, Node.js, Python, you name it) to know exactly what to look for. We document technical debt, security concerns, and scalability ceilings before writing a single line of code.

Requirements document. A detailed spec, not a vague feature list. User stories, acceptance criteria, data models, edge cases. You review it, push back where it’s wrong, and sign off before we move forward.

Architecture proposal. Our engineering leads design the technical architecture: which frameworks, how services talk to each other, where data lives, how the system scales. For AI agent projects this includes model selection (OpenAI, Anthropic, open-source), vector database choices, and token cost projections. For RAG systems it includes chunking strategy and retrieval architecture. For web applications it covers frontend framework, backend API structure, database schema, and deployment topology.

Why Discovery matters

We’ve watched companies skip this phase to “move fast.” They end up spending twice the budget fixing misaligned expectations. Discovery costs 1-2 weeks upfront and saves 4-6 weeks downstream. Every time.

Deliverables you’ll receive:

• Requirements document with user stories and acceptance criteria
• Technical architecture diagram
• Technology stack recommendation with rationale
• Project timeline with milestones
• Cost estimate (fixed-price or hourly projection)

Phase 2: Design (1-2 Weeks)

Design isn’t decoration. It’s the blueprint for how real people will use what we build, which means design decisions are product decisions.

What happens during Design

Wireframes. Low-fidelity layouts that map out every screen, every flow, every interaction. We use Figma, and you’ll have full access to comment, suggest changes, and iterate. Wireframes are cheap to change. Code is expensive to change. So we get alignment here first.

UI/UX prototypes. Once wireframes are approved, our designers build high-fidelity prototypes. These look and feel like the real product. You can click through them, test user flows, and share with stakeholders for feedback. For AI interfaces we pay extra attention to conversation flows, response formatting, and error states, because AI products need UI patterns that handle uncertainty gracefully.

Design system. Colors, typography, spacing, component library. Everything documented so the development team builds consistently. This matters more than people think. Without a design system, you get visual inconsistencies that quietly erode user trust.

User flows. We map every path a user can take. Happy paths, error paths, edge cases. What happens when the AI doesn’t have an answer? When the payment fails? When a user loses internet mid-form? We design for all of it.

Deliverables you’ll receive:

• Wireframes for all screens (Figma, shared access)
• High-fidelity UI prototypes (interactive, clickable)
• Design system documentation
• User flow diagrams

Phase 3: Agile Development (4-16 Weeks)

This is where the building happens. We run Agile with two-week sprints. Two weeks is long enough to deliver something meaningful, short enough to course-correct before you’ve burned a month going the wrong way.

How our sprints work

Sprint planning (Monday, Week 1). The team reviews the backlog, selects user stories for the sprint, and breaks them into tasks. Each task is estimated in story points. You’re invited to this meeting. You decide the priorities.

Daily standups (15 minutes, every day). Every team member answers three questions: What did I do yesterday? What am I doing today? What’s blocking me? You can join live or read summaries we post in your Slack channel. The point isn’t ceremony, it’s catching problems on day one instead of week three.

Development. Engineers write code, write tests, submit pull requests. Every PR gets reviewed by at least one other engineer before merging. We enforce coding standards, run automated linters, and maintain documentation alongside the code.

Sprint demo (Friday, Week 2). We show you working software. Real functionality running in a staging environment, not slides or mockups. You’ll test it, give feedback, and that feedback shapes the next sprint.

Velocity tracking. We measure how many story points the team delivers each sprint. After 2-3 sprints, velocity stabilizes and we can predict timelines with high accuracy. If we’re falling behind, you’ll know before it becomes a crisis.

Our tech stack

We match the technology to the problem, not the other way around:

• AI/ML: Python, LangChain, CrewAI, AutoGen, LangGraph, RAG pipelines, vector databases (Pinecone, Weaviate, ChromaDB)
• Backend: Laravel (60+ projects), Node.js/Express (50+ projects), Python/FastAPI
• Frontend: React, Vue.js, Next.js
• Mobile: React Native, Flutter
• Infrastructure: AWS, GCP, Azure, Docker, Kubernetes
• Databases: PostgreSQL, MySQL, MongoDB, Redis

What you’ll see during development

• A Jira board with every task, its status, and who’s working on it
• A staging environment updated after each sprint
• Sprint velocity charts showing progress over time
• Weekly video call with the project lead (30-45 minutes)

Ready to discuss your project? Talk to our team.

Phase 4: Quality Assurance

QA isn’t a phase that starts after development. It runs in parallel from sprint one. But before we deploy, we do a full final pass.

What QA covers

Unit tests. Individual functions and components tested in isolation. We aim for 80%+ code coverage on critical paths. For AI systems, this includes testing prompt templates, response parsing, and fallback logic.

Integration tests. Making sure the pieces work together. API endpoints return the right data. The frontend renders what the backend sends. Third-party integrations (payment processors, CRMs, AI APIs) handle real-world responses, including the ugly edge cases.

Load testing. We simulate real-world traffic patterns. If your app needs to handle 10,000 concurrent users, we test at 15,000. For AI applications, including voice agents running concurrent calls, we test throughput under load and measure response latency at various traffic levels. Skolaro, one of our longest-running projects, serves 1.5M+ users, so we’ve learned the hard way what load testing actually needs to cover.

Security audit. OWASP Top 10 checks at minimum. For applications handling sensitive data we go deeper: penetration testing, authentication flow review, encryption verification, API key management. If HIPAA or GDPR compliance is in scope, we have dedicated protocols for that.

User Acceptance Testing (UAT). You and your team test the application against the requirements document. We track every issue in Jira, prioritize by severity, and fix before deployment. UAT typically takes 1-2 weeks depending on project size.

Phase 5: Deployment

Deployment shouldn’t be stressful. With proper CI/CD, it’s routine. With improper CI/CD, it’s a Friday night nobody enjoys.

What deployment looks like

CI/CD pipeline setup. We configure automated build, test, and deployment pipelines using GitHub Actions, GitLab CI, or AWS CodePipeline, whichever fits your infrastructure. Every code push triggers automated tests. Passing builds deploy to staging automatically.

Staging to production. The staging environment mirrors production exactly. Once UAT passes on staging, we deploy to production during a planned maintenance window. For most web applications this means zero-downtime deployment.

Monitoring. We set up application monitoring (error tracking, performance metrics, uptime monitoring) before go-live. Sentry, New Relic, or CloudWatch, depending on your infrastructure. You’ll have a dashboard showing system health in real time.

Rollback plan. Every deployment has a documented rollback procedure. If something goes wrong post-deployment, we can revert to the previous stable version in minutes, not hours.

Deliverables at deployment:

• Production deployment with SSL, CDN, and monitoring
• CI/CD pipeline documentation
• Admin access and credentials
• Technical documentation and API docs
• Source code repository access (you own the code, always)

Phase 6: Support and Iteration

Launching is the beginning, not the end. Most products do their hardest learning in the first 60 days after they go live.

Post-launch support

30-day warranty. After deployment, we provide 30 days of free bug fixes for issues related to the original scope. Real bugs, not feature requests.

Monitoring and optimization. We watch performance metrics, error rates, and user behavior for the first 30 days. If page load times spike or an API endpoint starts timing out, we catch it before your users complain.

Feature iterations. Most products evolve after launch. We can continue on a retainer basis, building new features in the same sprint cadence. Many of our clients have been with us for years. Skolaro is in its 7th year of continuous development with us.

SLA-backed support. For production applications, we offer support SLAs with defined response times. Critical issues (system down): 1 hour response. High issues: 4 hours. Medium: 8 hours. Low: 24 hours.

Engagement Models

We offer three models because different projects need different structures. If you’re not sure which fits, our background and approach may help you decide.

Dedicated Team (Monthly Retainer)

Best for: Ongoing product development, projects lasting 3+ months, companies that want engineers embedded in their workflow rather than working at arm’s length.

How it works: You get a dedicated team, typically 2-5 engineers, a project manager, and a QA engineer, working exclusively on your project. They join your Slack, attend your standups, and become an extension of your in-house team.

Pricing: Monthly retainer based on team composition. A typical team of 3 mid-senior engineers + 1 QA + project management runs $12,000-$18,000/month. That’s roughly 60-70% less than hiring equivalent US-based engineers.

Minimum commitment: 3 months. Most clients stay 12+ months. Our 95% retention rate is what it is for a reason.

Time and Materials (Hourly Billing)

Best for: Projects with evolving requirements, R&D work, early-stage startups still finding product-market fit.

How it works: You pay for hours worked. We track time in Jira and share transparent timesheets weekly. Scope can flex. Add features, pivot direction, scale hours up or down.

Pricing: Junior developers at $15/hr, mid-level at $18/hr, senior at $20-22/hr, expert/architect at $25/hr, team leads at $30-35/hr. These rates are for dedicated, full-time allocation.

Minimum commitment: None, though we recommend at least 4-week engagements for meaningful output.

Fixed Price (Milestone-Based Payments)

Best for: Well-defined projects under $50K, MVPs with clear scope, projects where budget certainty matters more than flexibility.

How it works: We agree on scope, timeline, and total price upfront. Payments tie to milestones. Typically 20% at kickoff, equal installments at each major milestone, 20% at final delivery.

Pricing: Based on estimated effort from the Discovery phase. We pad estimates by 15-20% for unknowns because we’d rather come in under budget than ask for more money later.

Minimum commitment: Full project duration.

Let’s figure out the right model for your project.

Communication Cadence

Miscommunication kills more projects than bad code. Here’s how we keep it from happening.

Channel	Frequency	Purpose
Slack	Daily, async	Quick questions, updates, file sharing. We respond within 2 hours during business hours (9 AM – 6 PM PKT, which overlaps well with US mornings).
Video call	Weekly (30-45 min)	Sprint progress, blockers, decisions that need discussion. Recorded and shared.
Sprint review	Bi-weekly	Live demo of completed work. Your feedback drives the next sprint.
Executive summary	Monthly	High-level progress report: milestones hit, budget burn, upcoming priorities, risks.
Jira board	Always available	Real-time task status. You have full access to see what’s in progress, what’s done, what’s next.

We overlap with US Eastern Time by 5-6 hours (PKT is UTC+5), US Pacific by 2-3 hours. For European clients, the overlap is even better. Eleven years of distributed work has made timezone management a solved problem for us.

Timeline Examples

Every project is different, but here’s what typical timelines look like:

Project Type	Timeline	Typical Budget
MVP (web application)	8-12 weeks	$20K-$40K
AI chatbot with RAG	6-10 weeks	$15K-$50K
AI agent (single)	6-10 weeks	$20K-$40K
Multi-agent AI system	12-20 weeks	$60K-$120K
AI voice agent	8-14 weeks	$25K-$80K
Full SaaS platform	16-24 weeks	$50K-$150K
Mobile app (cross-platform)	12-16 weeks	$30K-$80K
Enterprise platform	24-40 weeks	$100K-$300K+

These include Discovery, Design, Development, QA, and Deployment. Support and iteration are ongoing.

What our clients say about working with us

We don’t have to sell our process. Our retention numbers do that. A few data points:

• Skolaro has been our client for 7+ years. They started as a startup, and we helped them scale to 1.5M+ users. That doesn’t happen if the process breaks down.
• KanbanZone went from concept to 50,000 active users on our MERN stack implementation.
• Grundsteuer Digital, a 7-partner consortium, trusted us with a SaaS platform handling German property tax compliance, a domain where accuracy is non-negotiable.

Our 4.9/5 rating on Indeed (64 reviews), 4.7/5 on Clutch, and 4.5/5 on Glassdoor (39 reviews) reflect how our team feels about the work culture. That directly impacts the quality of work you receive.

Start a conversation about your project.

Frequently Asked Questions

How do you handle scope changes mid-project?

On Time & Materials engagements, scope changes are straightforward. We reprioritize the backlog and adjust. On Fixed Price projects, we use a change request process: we estimate the impact on timeline and budget, you approve or reject, and we adjust the contract accordingly. We never start work on unapproved scope changes.

What happens if a team member leaves mid-project?

It happens. We mitigate it with documentation, code reviews, and knowledge sharing practices. Every project has at least two engineers who understand the full codebase. If someone leaves, we backfill within 1-2 weeks and the new engineer ramps up from existing documentation. In 12 years, we’ve never had a project derailed by attrition.

Can we interview and select team members?

Yes, absolutely. For Dedicated Team engagements you’ll interview candidates, review their portfolios, and choose who joins your team. We typically present 2-3 candidates per role so you have options.

Do we own the source code?

100%. You own everything we build: source code, documentation, design files, all of it. We don’t hold code hostage. You’ll have full access to the GitHub repository from day one.

What’s your typical team composition for a project?

For a mid-size project ($30K-$80K), a typical team is 1 project manager, 1 senior engineer (tech lead), 1-2 mid-level engineers, 1 QA engineer, and 1 designer (during the Design phase). For AI projects, we add a dedicated ML engineer.

How do you ensure code quality?

Code reviews on every pull request, automated testing in CI/CD, coding standards enforced by linters, and regular architecture reviews. We also do periodic code audits looking at technical debt, performance bottlenecks, and security vulnerabilities, and address them proactively rather than letting them accumulate.