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🤓 Latest Submissions
Pantheon — AI Agent Security Operations Center
As enterprises deploy AI agents across finance, HR, and engineering, they face a critical blind spot — nobody knows what those agents are actually doing. A single manipulated prompt can leak credentials, exfiltrate data, or trigger unauthorized actions. Pantheon is the trust layer that fixes this. What Pantheon Does: Pantheon deploys three enterprise AI agents (FinanceBot, MedBot, DevBot) powered by Google Gemini 2.5 Flash, with every single interaction routed through Veea's Lobster Trap deep prompt inspection proxy. Every prompt and response is analyzed in real time for injection attacks, data exfiltration, PII requests, malware generation, and role impersonation — before anything reaches the model or the user. Key Features: Live SOC dashboard showing all agent activity in real time Full DPI security metadata on every interaction — risk scores, intent classification, threat signals Built-in red-team attack simulator — fire adversarial attacks and watch them get blocked live Complete audit trail with forensic detail for every interaction Natural language querying over audit logs Compliance-ready export for SOC2/HIPAA audit trails Security Layer: Every agent interaction is proxied through Lobster Trap with ingress and egress inspection. Prompt injection, data exfiltration, malware requests, and PII extraction are detected and blocked in sub-millisecond time with full forensic metadata returned on every request. AI Layer: All three enterprise agents are powered by Gemini 2.5 Flash via the OpenAI-compatible endpoint, enabling fast, accurate responses with enterprise-grade system prompt enforcement. The Problem is Real: Gartner predicts 25% of enterprise breaches by 2028 will involve AI agent abuse. Pantheon is the category-defining response — a purpose-built security operations center for the agentic enterprise.
19 May 2026
AxionSys - Local-first AI debugging intelligence
AxionSys is a completely offline, local-first AI debugging assistant built for developers who need deep code analysis without compromising privacy or relying on cloud APIs. Built and optimized to run on consumer hardware (like AMD Radeon GPUs via ROCm and Ollama), AxionSys acts as an autonomous debugging expert that sits right on your machine. The Workflow The system takes two inputs: a repository (either a local directory or a pasted GitHub URL) and an error log, traceback, or simple error message. AxionSys parses the log to extract structured queries and immediately prioritizes any files mentioned in the traceback. It then searches your entire codebase using a highly accurate Hybrid Retrieval system, combining dense vector embeddings (FAISS) with sparse keyword matching (BM25) to find the most relevant code chunks. Intelligent Analysis Instead of just returning search results, AxionSys uses an advanced LLM reranker with dynamic fusion scoring to guarantee the most relevant files are pushed to the top. The context is then passed to a Root Cause Engine powered by a local Qwen 3.5 9B model. The engine performs causal chain reasoning to trace how a bug propagates across multiple files, mapping out the precise call chain from [OK] to [BUG] to [CRASH]. Actionable Outputs AxionSys doesn't just tell you what went wrong; it tells you how to fix it. The final output provides: A plain-English Root Cause Analysis explaining the exact failure point. A Call Chain Visualization showing how the error cascaded through your architecture. A concrete Unified Diff Patch that can be directly applied to your code. Confidence Scores for both the diagnosis and the generated fix. Complete with an intuitive React frontend and a robust FastAPI backend, AxionSys offers enterprise-grade AI debugging with zero cloud dependencies, zero latency from network calls, and absolute data privacy.
10 May 2026
