Overview
AgentOps-360 transitions corporate legal workflows from passive chatbot "copilots" into a proactive, fully autonomous decision-making engine built for real enterprise utility.
The Problem: Enterprise procurement managers waste up to 15 hours manually verifying dense, multi-page vendor agreements. Under heavy deadline pressures, it is incredibly easy to miss hidden auto-renewal traps, ambiguous service level agreements (SLAs), and severe data privacy liabilities.
Our Solution: AgentOps-360 provides a clean, single-file drop interface that autonomously extracts raw text, maps legal risks into prioritized structured data tables, and delivers an explicit, validated Go/No-Go directive with concrete risk mitigation advice.
The Stack & Architecture: Deployed natively on isolated, high-performance Vultr Cloud Compute VMs for low latency and fixed hosting costs. To bypass open-source token limits under heavy enterprise traffic, we designed a parallel Map-Reduce workflow. The system chunks a 10-page PDF locally into 2-page text matrices, streaming them through the Featherless.ai gateway using an optimized open-source Mistral-7B-Instruct model layer. The platform enforces a Zero-Data-Retention posture in volatile RAM buffers, ensuring full compliance with GDPR and the EU AI Act.
Note: the demo URL is substituted with the GitHub repository link.
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