Sold by: Provectus
An AI powered, spec-driven software development consulting offer built on AWS that helps engineering, data, and AI organizations operationalize AI coding agents with governance, structured specifications, and enterprise-grade development workflows. Integrates Amazon Bedrock-backed AI governance, permanent project memory, and explainable AI-assisted engineering to improve code quality, accelerate delivery, and reduce AI-generated rework.
Overview
AI SDLC is a spec-driven AI software development consulting offer built on AWS that helps engineering, data, and AI teams operationalize AI coding agents with governance, structured workflows, and durable project context. Using Provectus’s spec-driven methodology, the solution creates permanent, searchable specifications across product, architecture, technical, and task layers, enabling AI coding assistants to work from governed project context instead of transient chat history.
Built around Amazon Bedrock for governance and security, AI SDLC supports tools like Claude Code, Cursor, and Kodu while integrating with existing repositories, CI/CD pipelines, and project-management systems through APIs and MCP-enabled integrations without requiring replatforming. The engagement combines workshops, retrieval-augmented AI reasoning, and implementation support to help organizations reduce rework, improve software quality, accelerate onboarding, and establish compliant AI-assisted engineering practices at enterprise scale.
Highlights
- Governed AI coding workflows. Routes AI coding agent traffic through Amazon Bedrock to provide governance, security, compliance controls, and enterprise oversight for AI-assisted software development activities.
- Permanent project memory. Establishes a searchable, shared specification framework where project knowledge lives in documentation rather than transient chat sessions, improving continuity across teams and development cycles.
- Enterprise integration without replatforming. Connects existing repositories, project-management systems, CI/CD pipelines, APIs, and MCP-enabled systems of record through AWS-native and MCP-enabled integrations while supporting existing AI coding tools and engineering workflows.
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