MarcoPolo Digest
Insights, updates, and perspectives from the world of enterprise AI.
Data Gateway Use Cases: Direct MCP from AI to SaaS
An account executive connects Claude straight to Salesforce using access IT already granted, and three things stop being visible the moment it works: API consumption, what data left the system, and why. First in a six-part series on how AI agents already reach into enterprise SaaS.
Data Gateway Use Cases: AI to SaaS and Data Warehouse
An account executive connects the same agent to Salesforce and Snowflake, and the same question can come back with two different answers, decided silently by whichever schema the model reads first. Second in a six-part series on how AI agents already reach into enterprise SaaS.
Ai4 2026: Why AI Agents Need a Data Gateway
Our co-founder, Aseem Chandra, explains at Ai4 2026 why AI agents need one checkpoint in front of enterprise systems for scoped credentials, governance, and a clear audit trail.
The data gateway for AI agents.
MarcoPolo whitepaper on the data gateway for AI agents — connect agents to operational systems and warehouses without giving up performance, governance, or trust.
BI needed a warehouse. AI needs a gateway.
BI centralized data so people could decide. Agents act instead of handing insights to someone else, and that changes what enterprise data infrastructure is for: federated access, runtime governance, and context across every operational system.
Enterprise AI is Raring to go. Are IT leaders Ready?
CEOs are pushing enterprise AI adoption. Learn what IT leaders must do to enable AI at scale — from data governance to context management and token costs.
MarcoPolo, A Workspace for AI to Work with Your Data
Most teams are using AI wrong. Claude and ChatGPT can reason — but can they touch your databases and CRMs securely? Aman & Aseem reveal the missing layer between AI and real-world data.
$11.5B Says The AI Model Isn't The Hard Part
OpenAI and Anthropic just bet $11.5B that the bottleneck for enterprise AI isn't model quality — it's deployment, talent, and the data context layer. What that means for every CTO whose vendor wants to live inside their org.
Where Enterprise AI is Actually Stuck: Data and Security
The real bottleneck for enterprise AI isn't the model — it's the layer where identity, data, and infrastructure intersect. Insights from 200 conversations at AI Dev SF 2026.
