Unlocking the Future of Enterprise AI: Bridging Gaps with Credal
Enterprise AI is on the rise, fueled by chat-based LLMs like ChatGPT, but it faces a crucial limitation: isolation. These AI agents need context from various tools and data to be effective.
Key Insights:
- Piecemeal Problem: Many organizations use disparate AI products, leading to inefficiencies. Agents function in silos without access to integrated data.
- The Collaboration Tax: As companies grow, communication becomes cumbersome, hindering productivity. AI has the potential to streamline these interactions if effectively implemented.
- Model Context Protocol (MCP): While MCP serves as a bridge for AI agents to connect with tools, it doesn’t solve governance and security challenges unique to enterprises.
Credal aims to fill this gap by providing an infrastructure layer that supports:
- Authorization: Ensuring agents access only approved data.
- Context Management: Equipping agents with essential organizational knowledge.
- Governance and Auditability: Tracking actions and maintaining compliance.
Embrace the future of AI with Credal! Join the conversation and share your thoughts below!
