Request Your Personalized Quotation
We’ll prepare an individual offer tailored to your startup’s needs
We’re happy to make an individual proposal for your startup! To ensure our quotation is accurate and meaningful, we need to understand your product, your team, and your current stage. The more context you share, the more precisely we can design a solution that fits your goals and budget. If you’re not sure about some details yet — no worries. Just describe what you have in mind, and we’ll help you shape the technical vision together.
Guidelines for Description:
Here are some ideas on what to include in your project description:
Here are some ideas on what to include in your project description:
- What your product does: describe its functionality, main purpose, and users.
- Your current stage: idea, prototype, MVP, beta, or live product.
- Your technical team: number of people, main roles (e.g., developers, data scientists, DevOps engineers).
- Technologies or platforms you use or plan to use: e.g., AWS, Azure, GCP, Python, Node.js, etc.
- The results you expect from us: e.g., cloud setup, automation, CI/CD pipelines, MLOps support, monitoring, or cost optimization.
Example Description (fictional sample):
We are developing a SaaS platform for small e-commerce shops that helps them track customer orders and predict inventory needs using machine learning. Currently, our product is in beta with ~500 test users. We have 3 backend developers and 1 data scientist. Our infrastructure is on AWS but not fully automated. We need support with CI/CD setup, cost optimization, and an MLOps pipeline for retraining models automatically. Ideally, we’d like to launch a stable production environment within 4 weeks.
We are developing a SaaS platform for small e-commerce shops that helps them track customer orders and predict inventory needs using machine learning. Currently, our product is in beta with ~500 test users. We have 3 backend developers and 1 data scientist. Our infrastructure is on AWS but not fully automated. We need support with CI/CD setup, cost optimization, and an MLOps pipeline for retraining models automatically. Ideally, we’d like to launch a stable production environment within 4 weeks.
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