Sdlc Orchestrator
Live interactive sandbox environment.
The Vision: AI-Driven Software Delivery
The SDLC Dashboard isn't just a development tool; it's a completely autonomous, multi-agent orchestrator. Built on our proprietary "Clean Core" architecture, it transforms high-level business requirements into verified, tested, and containerized applications.
By separating the Main Agent (secure operations) from Sub-Agents (risky, isolated tasks), we ensure maximum security while accelerating the delivery lifecycle by orders of magnitude. This platform eliminates developer bottlenecks, prevents AI hallucinations through strict citation verification, and delivers a human-in-the-loop sandbox for final approval.
🧠 AI Capabilities & Integration
Autonomous Multi-Agent Pipeline
Instead of relying on a single AI, we deploy a specialized swarm. The Project Manager Agent parses requirements, the Plan Agent generates execution manifests, and the Coding Agent executes the build.
Context & Retrieval Engine
The Retrieval Agent uses semantic search to build exact Context Briefs, while the Context Engine performs pre-flight memory recall of past mistakes to ensure previous bugs are never repeated.
Zero-Hallucination Governance
An independent Citation Agent verifies that all generated code is grounded in real, existing files. If it can't cite the exact file, the code is rejected.
Automated QA & Secure Sandboxing
Once code passes citation, the QA Agent writes and executes tests. Finally, the Sandbox Deployment Agent automatically containerizes the application for secure, immediate human testing.
⚙️ Functional Requirements
Requirement Breakdown
Users can input multi-stack, high-level requirements which are automatically broken down into isolated SDLC sub-projects.
Execution Manifests
Automated generation of step-by-step build plans for transparency and auditing.
Codebase Grounding
Semantic and lexical search against existing codebase and documentation to ensure AI context is 100% accurate.
Automated Verification
Continuous logical correctness testing run natively against modified code.
One-Click Review
Automated deployment of Dockerized sandbox environments for stakeholder/human review and final approval.
A closer look at the workflow.
Master the orchestrator step-by-step. Every component is designed to give you total control over the autonomous lifecycle.
Secure Login
Navigate to the demo link and click the Login button located in the navigation menu to enter your credentials securely.
Setup Workspace
Go to the Integration page. Here, you can easily add new Users, assign Team Members, and configure your active Sprint.
Connect to Context
Open the Chat Interface. Use the dropdown menus to select specific Azure Projects and Repositories, grounding the AI directly in your codebase.
View Work Items
Check the Work Items panel. High-level requirements are displayed here as actionable, trackable cards broken down by the Project Manager Agent.
Trigger AI Agents
Click the Execute button on any work item. This launches the autonomous multi-agent pipeline to plan and write code for that specific task.
Monitor Progress
Open the Agent Terminal to watch the agents in action. You will see their real-time thought processes, commands, and steps.
Review Code
Once the agents complete the task, open the Diff Viewer to see a clear side-by-side comparison of the code changes for human review.
Interested in this Demo?
Contact our sales team to get access to a private enterprise environment.
Contact Sales