From product discovery to growth marketing.

RaftLabs offers product discovery, prototyping, MVP development, enterprise application development, AI and automation, modernization, and growth marketing. Every engagement starts with a scoping sprint that produces a fixed price and timeline before development begins.

Pick the work you want done. If the strategy still needs a test, start with product discovery. If you need to click through the risky part first, that's prototyping. If you know the first version real customers should use, that's MVP development. If the company has to run the software, including permissions and integrations, that's enterprise application development. If a repetitive job or an AI agent should do the work, that's AI and automation. If the software you have is hard to change, that's modernization. If the product needs customers, that's growth marketing.

If you need senior engineers inside your team instead of a scoped project, that's a dedicated team. If more than one of these sounds right, tell us the problem on a 30-min call. We'll recommend the approach that fits.

Yes. Taking over an existing prototype, an inherited codebase, or a half-built product from a previous agency is a common starting point for us, alongside legacy modernization and adding AI capabilities to software that already exists.

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 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.

Yes. Dedicated engineers embed directly into your existing team by discipline: frontend, backend, DevOps, or QA. They work in your tools, join your standups, and are matched to your stack within a week, with no recruitment overhead or long notice periods.

This also works alongside a scoped project: our team can own a defined piece of work end to end while coordinating with your in-house engineers on the rest, rather than requiring you to hand over the whole codebase.

Project pricing depends on scope, team size, and delivery requirements. Our planning ranges are $15,000–$35,000 for a basic MVP, $30,000–$60,000 for a standard MVP, and $55,000–$100,000 for a full application build. Complex platforms typically run $100,000–$160,000; enterprise builds run $140,000–$240,000. Minimum project engagement is $9,500.

For ongoing engineering capacity, public per-person pricing is approximately $6,000–$6,500 per month, with a minimum team engagement of $12,000–$15,000 per month. These are planning ranges, not a quote: discovery establishes the scope and delivery plan for your project.

For a scoped fixed-price project, we agree the price before development begins and discuss scope changes before proceeding. Request a 30-min call to discuss your requirements.

Timeline depends on the scope of the first release. Our planning ranges are 6–10 weeks for a basic MVP, 10–14 weeks for a standard MVP, and 14–20 weeks for a full application build. Complex platforms typically take 20–28 weeks; enterprise builds take 24–36 weeks, with larger programs extending beyond that.

Discovery defines the scope, architecture, dependencies, and release plan before development begins. Integrations, data migration, security requirements, and stakeholder availability all affect the schedule. We agree on milestones for design, development, testing, and launch against your specific scope rather than promise the same delivery date for every project.

Yes. We build AI agents and automation pipelines that handle invoice processing, support ticket routing, and document data extraction without manual entry, and we connect the systems you already run through API development, CRM/ERP integrations, and business-systems integration work.

Most effective engagements combine both: automation handles the structured, high-volume work, and AI handles exceptions and judgment calls. We help identify which problem needs which approach before scoping.