Vibe Coding uses natural-language instructions and AI coding tools to generate, modify and iterate software quickly. Rudrriv turns that approach into a managed professional service: you share the outcome, users and constraints; Rudrriv coordinates the right delivery professionals, keeps the work inside an agreed scope, reviews the implementation, manages feedback and prepares the final delivery.
The service is most useful when you need to validate an idea, demonstrate a product flow, build an internal tool, connect a small number of systems, rescue an AI-built prototype or create an MVP foundation before committing to a larger engineering programme.
Share the product objective, target user, must-have workflow, priority features, reference interfaces, existing repository or builder project if one exists, required integrations, sample data where appropriate, access limitations, target deadline and any security, privacy or compliance constraints. Clear priorities matter more than a long specification: the goal is to identify the smallest build that can answer the business question you need to test.
Clarify the user problem, must-have flow, package fit, constraints, integrations and success criteria.
Use AI-assisted coding and professional judgment to create the agreed workflows in reviewable increments.
Test the main flow, review feedback, address in-scope issues and improve weak states before approval.
Prepare the agreed environment, source/repository delivery, setup notes, limitations and next-step guidance.
Vibe Coding can compress the time between an idea and a working build, but speed does not remove engineering responsibilities. Authentication, permissions, database rules, secrets, third-party APIs, payment logic, error handling, accessibility, performance and deployment configuration all need context-aware review. Rudrriv therefore treats AI generation as part of the workflow—not as a substitute for validation.
Choose the package by the complexity you need to validate now. The differences are based on workflows, screens, data/integration depth, testing, deployment and handoff—not just delivery speed.
| Included |
₹9,999
Essential
Proof Sprint
A focused Vibe Coding sprint for validating one core workflow with a working, reviewable prototype. |
₹24,999
Professional Recommended
MVP Build
A connected MVP for the most common founder or business requirement, with deeper flows, data and integration support. |
₹49,999
Advanced
Launch Foundation
A broader production-minded MVP foundation with multiple workflows, integrations, technical cleanup and a stronger handoff. |
|---|---|---|---|
| Core workflows | 1 | Up to 2 | Up to 3 |
| Key screens / states | Up to 3 | Up to 6 | Up to 10 |
| Requirements & scope map | ✓ | ✓ | ✓ |
| Responsive web implementation | ✓ | ✓ | ✓ |
| Authentication / data flow | — | 1 auth or data-backed flow | Auth + database workflow |
| External integrations | — | 1 | Up to 2 |
| QA depth | Core-flow QA | Functional + edge-case QA | Functional + regression + readiness QA |
| Deployment | Preview / staging | Staging deployment | Configured production handoff |
| Source / repository handoff | ✓ | ✓ | ✓ |
| Documentation | Short handoff note | Setup + continuation notes | Technical handoff + next-step roadmap |
| Revision rounds | 1 focused revision | 2 revision rounds | 3 revision rounds |
| Standard delivery | 4 business days | 7 business days | 12 business days |
| Package price | ₹9,999 | ₹24,999 | ₹49,999 |
Package pricing is for the defined scope above and is inclusive of taxes. Hosting, paid APIs, model usage, third-party subscriptions, premium components, regulated-data requirements and work outside the package limits are not included unless confirmed in the final scope.
The service is designed for bounded product questions where a working build is more useful than a slide deck. Larger or higher-risk applications should be scoped as a custom engineering engagement.
Validate a core sign-up, workflow or value proposition before funding a broader product build.
Turn a spreadsheet-heavy or manual process into a small application teams can test in real operations.
Create a functional portal flow for stakeholder review, onboarding tests or early customer feedback.
Demonstrate how a selected API, automation or data source can support a practical business workflow.
Test an AI-assisted product interaction, workflow or interface before committing to a full platform architecture.
Stabilize an existing AI-built project that needs debugging, cleaner logic, better responsiveness or a clearer handoff.
Our Vibe Coding brief was fairly specific, and the team picked up the context quickly without forcing us through unnecessary process. The core of the engagement was a rapidly built working product prototype, and the team avoided distracting us with features that were outside the goal. The quality showed most clearly in the way they handled fast iteration, AI-assisted coding, code quality, feature validation, deployment, and technical cleanup. Testing was more thorough than our previous internal attempts, especially around edge cases and real usage. The biggest improvement was a fast prototype that proved the concept while still leaving us with code we could continue developing. The engagement saved us several rounds of trial and error and gave us a cleaner baseline for future work.
Our previous attempt at Vibe Coding had left several loose ends, so we wanted a more disciplined second pass. They delivered a rapidly built working product prototype and kept the work aligned with the original business need. We were particularly happy with the attention to fast iteration, AI-assisted coding, code quality, feature validation, deployment, and technical cleanup. Feedback was incorporated carefully, and completed work did not keep regressing after each revision. The completed work gave us a fast prototype that proved the concept while still leaving us with code we could continue developing. There were no surprises at handoff, and the system behaved the way it had during review.
We brought in the team for Vibe Coding because we wanted a production-minded implementation, not just a proof of concept. Their job was to produce a rapidly built working product prototype, and they handled both the visible work and the less obvious technical details behind it. The team made strong decisions around fast iteration, AI-assisted coding, code quality, feature validation, deployment, and technical cleanup and explained the reasoning when we asked. The project stayed organized even when we introduced new information midway through the work. By launch, we had a fast prototype that proved the concept while still leaving us with code we could continue developing. The engagement saved us several rounds of trial and error and gave us a cleaner baseline for future work.
Tell us what you want to validate or build, where the project stands today, and what needs to work at handoff. Rudrriv will review the requirement and map it to the most suitable package or custom scope.
