Fatin Ruhul Shahazad@faz3d
faz3d
🤓 Latest Submissions
Risk Horizon: Supplier Risk AI Agent
Risk Horizon is a multi-step AI agent for supplier risk and market disruption intelligence. Companies often depend on critical suppliers, logistics providers, manufacturers, and raw material sources, but early warning signs of disruption are scattered across the public web. Risk Horizon helps teams detect those signals faster by using live web data to search for supplier-related news, advisories, regulatory updates, market commentary, and disruption reports. The agent collects relevant sources, analyzes them for risks such as delays, shortages, sanctions, lawsuits, price changes, factory issues, and geopolitical events, then generates a source-backed risk report. Each report includes a risk score, confidence level, warning signals, business impact, source evidence, and recommended actions. Risk Horizon is designed for procurement, supply chain, operations, and finance teams that need to act before supplier disruptions become expensive business problems.
31 May 2026
CXGuard - Powered by Lobstertrap
CXGuard is a security gateway and governance dashboard for AI-powered customer support agents. It is designed for companies that want to deploy AI support bots safely without exposing themselves to prompt injection, customer data leakage, refund abuse, secret extraction, policy manipulation, or unsafe automated actions. As more customer experience teams adopt AI agents to answer questions, resolve tickets, process returns, and reduce support costs, a new class of risk appears. Unlike traditional software, AI agents can be manipulated through language. A malicious customer may try to override the agent’s instructions, reveal hidden system prompts, extract private customer information, access internal policies, bypass refund limits, or trick the bot into performing actions it should not take. For enterprises, these failures are not just technical bugs — they can become privacy incidents, financial losses, compliance gaps, and reputational damage. CXGuard solves this by sitting between the customer support interface and the underlying language model. Every support conversation is routed through Lobster Trap, an inline prompt inspection and policy enforcement layer, before the request reaches the LLM. Lobster Trap inspects incoming prompts and outgoing model responses for risky signals such as prompt injection, credential extraction, personally identifiable information requests, sensitive file paths, role impersonation, unsafe commands, external exfiltration, and other suspicious patterns. CXGuard then turns those low-level security signals into an enterprise-ready product experience: clear decisions, risk scores, policy hits, incident details, human-review queues, and audit-ready logs.
19 May 2026
Ticket Intelli - CX Analysis Agent
Ticket Inteli is an AI-powered support ticket analysis agent designed to help support and engineering teams move from messy customer issue reports to clear engineering action faster. In many organizations, support tickets arrive with incomplete context, inconsistent wording, unclear severity, and vague customer impact. Before engineers can begin investigating, support teams often need to manually read the ticket, identify the affected product area, estimate business impact, summarize the issue, suggest possible root causes, and prepare a safe customer response. This process is repetitive, time-consuming, and inconsistent across teams. Ticket Inteli solves this by transforming unstructured support tickets into structured engineering triage briefs. A user can paste a customer issue or select a sample ticket, click Analyze, and receive a clear breakdown that includes severity, business impact, likely product area, possible root causes, engineering handoff summary, recommended next steps, regression test suggestions, confidence score, estimated triage time saved, and a customer-safe response draft. The goal of Ticket Inteli is not to automatically fix code. Instead, it acts as an intelligent analysis layer between support and engineering. It helps teams understand what is happening, why it matters, where engineers should look first, and how support can communicate with customers professionally. This improves support-to-engineering handoff quality and reduces the time spent turning vague tickets into actionable technical work.
17 May 2026
OpsTune
OpsTune is an AI-powered industrial incident analysis system designed to help operations teams understand and act on technical incidents faster. In industrial environments, operator reports are often written as unstructured text, making it difficult to quickly identify severity, root causes, evidence, and next steps. OpsTune transforms these raw reports into structured, actionable intelligence using a fine-tuned large language model running on AMD hardware. The system takes a messy incident report as input and returns a clear JSON analysis including severity level, incident category, likely root causes, supporting evidence, recommended actions, confidence score, and a concise operational summary. This enables faster triage, better decision-making, and more consistent incident handling. Our goal is to demonstrate how domain-adapted AI workflows can improve industrial maintenance, reduce downtime, and support frontline teams with reliable, explainable incident analysis.
10 May 2026
