Timelines vary based on complexity. Proof of Concepts (PoCs) and basic RAG architectures take 2-4 weeks. Full-scale autonomous agents and custom model fine-tuning generally take 2-3 months to reach production-ready status.

No. We engineer everything custom for your specific use-case. While we utilize state-of-the-art foundation models and cloud infrastructure, the architecture, pipelines, and frontend interfaces are built from scratch to ensure maximum performance and security.

You do. All custom code, fine-tuned models, and architectures developed during our engagement are 100% owned by your company upon project completion and final payment.

We implement enterprise-grade security protocols, including end-to-end encryption, VPC isolation, and compliance-driven architectures. For highly sensitive data, we can deploy open-source models (like Llama 3) directly onto your on-premise servers so data never leaves your environment.

We offer transparent, fixed-price engagements based on project scope, rather than unpredictable hourly billing. Engagements typically start at ₹35K for basic web setups and scale to ₹5L+ for enterprise Gen AI deployments. You can use our AI Predictor on the Pricing page to get an estimate.

Yes, we offer flexible post-deployment SLA (Service Level Agreement) packages. These include 24/7 monitoring, regular model retraining, bug fixes, and infrastructure scaling to ensure your AI systems remain highly performant as your user base grows.

We believe in radical transparency. You will have a dedicated Slack/Teams channel with our core engineers, weekly sprint review calls, and a live Notion dashboard where you can track every task, milestone, and deliverable in real-time.

We don't use junior developers or offshore intermediaries. When you hire Buildlyst, you work directly with senior AI engineers, data architects, and full-stack developers who have built scalable systems for leading enterprises and high-growth startups.