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SelectedWork.
Agile ArtifactAnalyzer.
From requirement to merged code.
An AI platform that helps delivery teams produce high-quality agile artifacts — Epics, User Stories, and Tasks — faster and with greater consistency. It closes the loop from requirement definition to code delivery so every artifact meets professional standards before implementation begins.
1
Initial Analysis
Parse intent, extract criteria.
2
Senior Refinement
Refine against INVEST and SAFe.
3
Quality Evaluation
Independent scoring and gates.
KEY FEATURES
Three-Pass AI Pipeline
A sequential workflow with initial analysis, senior-level refinement, and independent quality evaluation.
Intelligent Analysis
Evaluates artifacts against INVEST, Scrum, and SAFe criteria with structured reports on clarity, business value, risk, and complexity.
RAG Grounding
Retrieval-Augmented Generation grounds evaluations in your company delivery standards and templates.
Ecosystem Integration
Deep integrations with Jira for one-click imports and write-backs, and Bitbucket for automated pull request creation.
Automated Code Generation
Generates production-ready TypeScript implementation files from the refined artifacts and acceptance criteria.
Idea toDeploy.
Rough concept to governed release.
A comprehensive platform that transforms rough concepts into working prototypes and cloud-ready deployments. Built for team-based collaboration, it emphasizes human-in-the-loop governance and strict compliance standards.
RBACEU AI Act
R01Viewer
R02Contributor
R03Reviewer
R04Approver
R05Maintainer
R06Admin
R07Owner
KEY FEATURES
Secure Infrastructure
All LLMs run through private AWS Bedrock infrastructure. No data is sent to public AI services or used for model training.
Role-Based Governance
Seven distinct organizational roles — from Viewer to Owner — manage permissions and approval workflows.
Human-in-the-Loop Workflow
AI agents execute tasks while the team retains decision power through multi-step approval and voting.
Governed Deployment Pipeline
Multi-environment Dev, QA, and Production releases with environment-specific governance on AWS and Azure.
Compliance-First Design
Engineered for strong adherence to the EU AI Act, embedding transparency and auditability into the core architecture.
PPE &Accessory ID.
Real-time safety, frame by frame.
A computer vision system for industrial environments that monitors compliance with safety protocols in real-time. It identifies both mandatory protective equipment and prohibited personal items to maintain high safety and hygiene standards.
KEY FEATURES
Comprehensive Detection
Identifies essential PPE including lab coats, hairnets, helmets, hearing protection, and masks.
Accessory Monitoring
Validates that operators are not wearing prohibited jewelry such as rings, watches, piercings, or necklaces.
Persistence Rule
Alerts only register if a condition persists for 20 frames (≈3 seconds) — minimizing false positives.
High Precision
Over 98% precision for large objects like helmets and coats. Over 90% for micro-objects like jewelry under optimal lighting.
Centralized Reporting
A secure cloud portal lets stakeholders review alerts, export reports, and monitor compliance trends across the facility.
The patterns behind the work.
Agents
Tool-use, memory, orchestration, and workflow automation.
RAG
Retrieval systems grounded in private business knowledge.
Vision AI
Image intelligence, detection workflows, and operational alerts.
Governance
Evals, audit trails, access controls, and responsible release gates.
