Building your product needs sustained engineering velocity, not just one good sprint. A Kovil AI dedicated development team gives you a complete, cohesive engineering pod — tech lead, full-stack engineers, DevOps, QA — working exclusively on your product under your direction.
When you add engineers one at a time, each new addition needs time to calibrate to the team. Communication patterns, code review standards, and technical decisions have to be re-established. The tenth week is better than the second, but you pay for the ramp every time.
A pre-formed dedicated team arrives already calibrated. The Tech Lead knows how the engineers work. The QA engineer knows what to test. Within 2 sprints, a Kovil AI dedicated team is at full velocity — not because they are smarter, but because they are already coherent.
For sustained product development, this is a significant advantage. A coherent team accumulates context faster, makes better architectural decisions, and has tighter feedback loops between design, development, and QA.
Three standard team profiles. All are customisable based on your stack, product phase, and workstream needs.
For early-stage MVPs or focused product modules.
Best for: MVP builds, v2 feature sprints, small product teams
For sustained product development with parallel workstreams.
Best for: Growing SaaS products, platform migrations, launch sprints
For enterprise products or multiple concurrent streams.
Best for: Enterprise product builds, AI platform development, multi-team programmes
Transparent, consistent delivery every sprint. No status ambiguity, no end-of-quarter surprises.
Week 1: Tech Lead audits existing codebase or designs greenfield architecture. Shared as a doc before sprint 2 begins.
Bi-weekly sprints with your product owner. Stories in your tool (Linear, Jira, GitHub Projects). No process overhead imposed.
Async daily standup updates in Slack or your comms tool. Blockers surfaced immediately, not buried until the next sync.
Every Friday the team shows what shipped. You see working software every week, not quarterly reports.
Continuous integration from day one. Automated tests, staging environments, and deployment pipelines set up in the first 2 sprints.
Team composition and process reviewed monthly. Scale up, swap specialisms, or adjust team structure as the roadmap evolves.
Tell us the product, the stack, and the phase. We will compose the right team and have them shipping within 3 weeks.
Compose My TeamA PropTech startup had a funded idea, a product manager, and no engineers. We assembled a 5-person dedicated team: Tech Lead, 2 full-stack engineers (React + FastAPI), 1 DevOps engineer, and 1 QA engineer. The team was operational in 16 days. Sprint 1 delivered the data model and CI pipeline. By week 14 they had shipped a production app with AI-powered property valuation, tenant matching, and document generation.
A dedicated development team is a pre-formed engineering pod — typically a tech lead, 2-4 developers, a DevOps engineer, and a QA engineer — assigned exclusively to your product or project. They work full-time on your work, under your direction, using your tools and processes. Unlike a project outsourcing model, you have full visibility and control. Unlike individual staff augmentation, you get a cohesive team that has already calibrated to each other.
A Kovil AI dedicated development team is typically operational within 2-3 weeks: 1 week to finalise team composition, 1 week for access provisioning and kickoff, and the team contributes from sprint 1. Compare this to building an equivalent in-house team, which typically takes 6-12 months of sequential hiring.
A 5-person in-house team (lead + 3 engineers + QA) in the US costs $900K-$1.4M per year in fully loaded salaries, plus $100K-$200K in recruitment fees and 6-12 months to assemble. A Kovil AI dedicated team provides comparable output, is operational in 3 weeks, scales flexibly, and has no recruitment overhead.
You do. The Tech Lead is your primary point of contact and manages the team day-to-day. You set the product vision, priorities, and success metrics. The Tech Lead translates these into sprint plans and technical decisions. Weekly status calls, daily standups, and access to your project management tools keep you fully informed.
Kovil AI covers: frontend (React, Next.js, TypeScript), backend (Python/FastAPI, Node.js/NestJS, Go), databases (PostgreSQL, MongoDB, Redis, Supabase), cloud (AWS, GCP, Azure), DevOps (Kubernetes, Terraform, GitHub Actions), and AI/ML integration (LangChain, OpenAI/Anthropic APIs, vector databases). We compose the team based on your stack.
Yes. We regularly send teams into existing codebases. The first sprint is typically a codebase audit and context-setting sprint: understanding architecture, identifying technical debt, and establishing coding standards alignment. This ensures the team can contribute cleanly from sprint 2 without introducing regressions or style inconsistencies.
Most dedicated team engagements run 6-18 months. Shorter engagements (3-6 months) suit well-defined product phases: an MVP build, a platform migration, or a major feature suite. Longer engagements suit companies with ongoing product roadmaps who want sustained velocity without the overhead of maintaining a large permanent headcount.
Yes. Kovil AI dedicated development teams can include AI engineers, LLM specialists, and ML engineers alongside full-stack developers and DevOps. Many clients start with a general product team and add AI specialists as the roadmap requires. See our Dedicated AI Team page for teams focused exclusively on AI engineering work.
Tell us what you are building and we will compose the right team, operational in 3 weeks.
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