How we engage
How We Work
From requirements and risk mapping through AI workflow design, build, testing, deployment, and production iteration — delivered as scoped outcomes with weekly demos.
Process
SursaTech runs an AI-native product engineering workflow — senior engineers paired with AI agents to design, build, test, and ship production software faster, without trading away quality. Engagements are scoped around product outcomes rather than billable hours: work ships on a monthly retainer with a live demo every week, so progress stays visible and priorities can shift between milestones.
Phases
1. Discovery & risk mapping. Frame the problem, identify the highest-risk assumptions, and agree the smallest meaningful outcome. 2. Architecture, AI workflow & validation. Pick the stack that fits the product (not the resume), design any agent/RAG/tool workflow, validate the approach against the risks, and lock the first milestone. 3. Build in milestones. Ship in weekly increments. Each demo is a real, working slice of the product. 4. Test critical flows. QA leadership sets the testing strategy from day one: Playwright/Cypress/Vitest, agent-orchestrated test generation, and the client's CI. 5. Deploy. Production-ready deployment paths on cloud-native infrastructure. 6. Operate & iterate. After first release, continue on the Operate retainer with weekly demos and production-feedback-driven iteration.
What clients see every week
A live demo of working software, a written summary of what shipped, what is next, and what risks have moved.