In high-velocity work environments, traditional performance management is fundamentally broken. Reviews are reactive, burnout is only detected after a resignation, and top talent is often only recognised once a year. Momentum transforms this cycle into a predictive intelligence engine. By leveraging Gemini and Supabase, Momentum ingests daily work metadata such as PR velocity and sentiment shifts to identify workplace trends in real-time. Unlike traditional dashboards, our "Executive Reasoning" layer delivers proactive, bias-aware coaching prompts. This allows leaders to intervene with empathy before a "deadline slip" occurs and ensures that "quiet geniuses" who drive the system from the shadows are recognised and retained. Security is foundational to our design. Our Privacy Vault ensures that personally identifiable information (PII) is masked by default, maintaining a zero-trust, GDPR-compliant environment. By bridging the gap between employee well-being and executive oversight, Momentum creates a sustainable culture of high performance, neutralising cognitive biases and saving firms millions in attrition costs. It is not just a tool for monitoring, it is a platform for human capital optimisation.
7 Feb 2026
As cyberattacks rise, SOC teams face alert fatigue and slow manual triage. Our AI-powered Tier-0 SOC Analyst workflow, built on Opus, automates intake, analysis, risk scoring, and reporting to cut false positives and improve efficiency. We built a simple UI where analysts can upload emails, syslogs, SIEM logs, file metadata, text, and URLs in formats like TXT, PDF, CSV, or direct links. The UI securely sends all inputs to Opus via API, ensuring wide coverage and strong integration. Opus extracts raw content and normalises everything into a unified JSON structure with reliable validation and retry logic. Large-scale IoC extraction identifies IPs, domains, URLs, hashes, and email IDs. Since external services were unreliable, we built a RAG module to classify suspicious or malicious patterns. All IoCs then go through an enrichment stage that adds context, reputation, threat tags, domain age, and confidence, producing a consistent enriched dataset. Two decision nodes handle triage: the first checks whether an IoC is malicious. Clean IoCs go straight to output for automatic report generation, while malicious ones are severity-scored and reviewed by AI. The second node checks if the severity is equal to or greater than 70. Lower scores generate tickets automatically; higher scores trigger human review before finalisation. AI review occurs at key stages—normalised data, enriched IoCs, severity, and final ticket—while human review is reserved for high-risk cases. The workflow ends by generating a report and audit trail, displayed on the UI for full visibility. The system aligns with the UAE and GCC visions in the Middle East by demonstrating a secure, efficient, and scalable AI-driven cybersecurity model. Note: Add our RAG PDF to the RAG Extraction input: https://drive.google.com/file/d/1HYgv4h4W0oWzx2wcMFyGerX1e-4Ba-X5/view Also generate your own PDF API key and add it to the Bearer Auth field in the Report and Audit Artefact Generation node.
19 Nov 2025
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