Partner with Caylent to design, build, and launch cloud-native applications your team can own.
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Design and ship cloud native applications that integrate natively with AI. From greenfield to production scale, faster.
Most software delivery failures aren't engineering failures, they're discovery failures. Ideas move from stakeholder to backlog without validation, and by sprint three, scope has bloated and the original deadline is already out of reach.
Cloud Native App Dev closes that gap. We combine structured product discovery with agentic engineering to build cloud-native applications your team can actually own, moving products to market in weeks instead of months, and months instead of years. From a validated idea to a production launch, or an MVP to a scalable release.
We don't hand off a codebase and disappear. We build with your team, so they can extend what we build together.
Cloud Native App Dev looks different depending on where you sit. Technical leaders see architecture decided before Sprint 1. Product leaders see a shorter path from idea to shipped feature. Business leaders see the vision turning into measurable business value. The shift is the same: from unvalidated builds to value.
Architecture decisions get made before Sprint 1, not under deadline pressure. IaC, CI/CD, and observability are baked in from day one.
Stop building what gets asked for. Start building what users need, with a backlog that's sprint-ready, not strategy-ready.
Every dollar funds a validated roadmap and turns into measurable business outcomes.
We build with AI as both a product capability and a delivery advantage, powered by AWS Bedrock and Anthropic's Claude, moving products to market in weeks instead of months.
Map user journeys, review existing artifacts, and validate the assumptions behind the ask; surfacing the real problem before we design a solution.
Wireframes and clickable prototypes, validated with business stakeholders. The input shapes the epics, sized, prioritized, and trimmed down to exactly what the MVP needs to launch.
Define the technology backbone, integration points, and team structure needed to deliver, mapped into a feature-to-sprint roadmap.
Present the product vision, timeline, budget, teaming model and ramp-up plan. Prepare for the build phase.
A decision guide for AWS teams on choosing between Claude Platform on AWS, Amazon Bedrock, and Claude Enterprise, with migration considerations for existing Bedrock users.
Learn why 85% of AI projects fail and how strategic UX design drives trust, adoption, and measurable ROI.
Learn how organizations can successfully turn their internal tool into a commercial product.
AI coding tools have made it easy to prove a concept in days. But the same speed that makes a prototype possible also hides the gap, no error handling, no auth model, no path to scale. That gap is where these builds stall. We close it with AI-accelerated engineering across the full SDLC, not just faster code, so what takes other teams months takes weeks.
Validate the problem, define the product vision and roadmap. Leave with T-shirt-sized epics and a cleare path forward.
Already validated the problem? Product Launchpad builds on the Discovery and delivers a sprint-ready backlog for Sprints 1 & 2, with no additional refinement needed - all in a single motion.
Cloud Native App Dev runs on a consistent team that stays with you from the first workshop through launch, not a rotating cast handed off between phases.
Need deeper product strategy or experience design work? See Product Strategy & Experience
