Custom software development & AI services. We scope your problem — not our menu.

Custom software development at RaftLabs is priced on a fixed-project basis after a one-week discovery sprint, not an open-ended hourly rate. Typical ranges: small web applications with 4–5 core features run $15,000–$30,000; mid-sized platforms with 6–9 features run $30,000–$65,000; complex enterprise systems with 10+ features start from $75,000.

AI and automation projects vary by complexity: simple chatbots start around $15,000; autonomous AI agents with multiple integrations run $30,000–$80,000; full AI platform builds can exceed $100,000. Voice AI deployments typically cost $20,000–$50,000. Mobile apps run $25,000–$70,000 depending on platforms and features.

The fixed price is agreed before development starts. It does not change unless scope changes, and any scope change is discussed explicitly before we proceed. To get a specific number for your project, book a 30-min call. We scope it properly before you commit to anything.

Most custom software projects at RaftLabs ship in 10–14 weeks from discovery to production deployment. The breakdown: Week 1 is discovery (stakeholder interviews, workflow mapping, scope definition). Weeks 2–3 cover design (wireframes, architecture, fixed-price agreement). Weeks 4–12 are development in bi-weekly agile sprints. Weeks 12–16 cover QA, load testing, and deployment.

AI and automation projects typically run 8–12 weeks. Voice AI agents deploy in 6–10 weeks. Mobile apps take 10–14 weeks. Complex enterprise builds extend to 16–20 weeks. We've shipped 100+ products on these timelines since 2020. Our average delivery is 12 weeks. We publish this number because we've earned it across project types and industries.

Process automation uses deterministic logic to eliminate manual steps in a defined workflow: if X happens, route it to Y, send notification Z. It works well for structured, predictable tasks: invoice routing, data sync between systems, report generation. It is faster to build, cheaper to run, and easier to audit.

AI development handles tasks that require judgment, pattern recognition, or unstructured input. An automation routes invoices by template matching; an AI agent reads invoices in any format, extracts the right fields, and flags anomalies even in documents it has never seen. AI is the right choice when the input is variable, the rules are too complex to enumerate, or the system needs to improve over time.

Most effective projects combine both: automated pipelines handle the structured, high-volume work; AI handles exceptions and judgment calls. We help clients identify which problems need AI versus automation before scoping. The former is more complex and expensive; the latter is often the right answer.

All project work is priced at a fixed cost agreed before development starts. This means you know the exact cost before committing, and it does not change unless scope changes explicitly. We do not do time-and-materials or open-ended retainers for project delivery.

The fixed price is set after the discovery sprint (Week 1), which maps the full scope, produces low-fidelity wireframes, and gives us the information to quote accurately. The discovery sprint itself is a paid engagement, typically $2,000–$5,000 depending on project complexity. The cost applies toward the full project if you proceed.

For dedicated development teams (staff augmentation), we charge a monthly rate per engineer: typically $6,000–$12,000 per month for a senior developer depending on specialisation and seniority. Contracts are monthly with no minimum commitment.

You need a clear understanding of the business problem. You do not need wireframes, a technical spec, or a detailed feature list. Coming in with a rigid spec often creates more problems than it solves, because it locks in a solution before we understand the problem.

The most productive starting point is a plain-language description of what is costing you money or time: 'my team spends 20 hours per week manually entering data from PDF invoices into our ERP' or 'we lose leads because nobody answers the phone after 5pm.' From that, we handle everything: discovery, scope definition, architecture, design, and build.

If you have an existing codebase, previous designs, or a technical team we need to coordinate with, that is useful context, but not a prerequisite. We start with a 30-min call to understand the problem and tell you honestly whether we are the right fit.

We have built software across a wide range of industries: healthcare, fintech, hospitality, logistics, manufacturing, legal, media, e-commerce, retail, education, martech, loyalty and rewards, travel, and professional services.

Clients include Vodafone, T-Mobile, Energia, Aldi, Cisco, Lockheed Martin, Wells Fargo, and Nike. Industry experience matters because domain knowledge shapes architecture decisions: a healthcare platform needs HIPAA compliance and audit trails; a fintech system needs fraud detection and real-time transaction logging; a logistics app needs offline mobile support and GPS integration. We bring that context from previous builds in your space.

If your industry is not on this list, it does not mean we cannot help. It means we will ask more questions in discovery to close the knowledge gap before we propose a solution.

Fixed scope and fixed price eliminate the most common cause of late delivery: scope creep. Within that fixed scope, bi-weekly agile sprints give you working software throughout. You see the product every two weeks, not at the end of a 14-week silence.

QA testing runs alongside development, not after it. Automated test suites, API testing, and manual QA are included in the project cost, not an add-on or afterthought. Every sprint ends with a demo. Any quality issue that surfaces during a sprint is fixed in that sprint before new work starts.

We have shipped 100+ products since 2020 with an average delivery of 12 weeks. Our project managers have direct authority to raise scope or timeline concerns without waiting for a steering committee. If something is going to affect delivery, you hear about it the same day we know, not in the next weekly report.

Yes. Legacy modernisation, performance remediation, adding AI capabilities to existing software, and inheriting a half-built product from a previous agency are all common engagements for us.

We start with a technical audit: code quality review, architecture assessment, security scan, and performance profiling. The audit gives you an honest picture of what you have: what is salvageable, what needs to be rewritten, and what can be improved incrementally. We give you a clear recommendation before quoting any work.

We do not take over codebases blindly. If the audit reveals the system is too fragile to extend safely, we will tell you, along with a realistic cost comparison between remediation and rebuild. Post-launch maintenance and ongoing development retainers are available for systems we have built or inherited.

We pick technology based on the problem, not what we are most comfortable with. That said, our primary stacks: for AI: Python, LangChain, LlamaIndex, OpenAI, Anthropic Claude, Mistral, Whisper, ElevenLabs, Deepgram; for web: React, Next.js, Node.js, TypeScript, PostgreSQL, Redis, Supabase, AWS, GCP, Vercel; for mobile: React Native, Swift (iOS), Kotlin (Android); for automation: custom Python pipelines, n8n, Make.

If you have an existing codebase in a specific stack: Ruby on Rails, Django, Laravel, .NET, we will work in it rather than pushing you to rewrite. The goal is solving your problem, not advocating for our preferred tools.