Governed workspace so AI works with your internal data.
Connect once, govern it centrally, and keep your context portable across every model your teams run.
The teams getting the most from AI prioritized data integration first.
Agentic AI rollouts today share three leaks at the root: token waste, wrong answers, and data exposure. Here's how MarcoPolo fixes them.
Naive MCP burns tokens
Native MCP reruns schema discovery on every query: up to 98.7% of token spend becomes overhead. Context built once in MarcoPolo reduces cost and query time as the workspace grows.
Wrong answers prompt retries
When the model lacks context, wrong answers send users back to reprompt. MarcoPolo seeds every workspace with your actual data, so responses land right the first time.
Sprawl scales with headcount
As teams grow, every per-user MCP connection adds one more surface to audit and one more credential path to manage. MarcoPolo consolidates that sprawl into a single workspace IT controls.
What running AI on your own terms gets you.
Own your context
Your schemas, business logic, and connections live as a versioned workspace in your own cloud, never trapped inside a vendor platform. It compounds with every query and stays yours to export, audit, or reuse.
Versioned · Exportable · In your cloudKeep control
Credentials stay scoped per user and never reach the model's context window. Every tool call is logged and streamed to your SIEM, so security reviews the architecture once instead of vetting each new AI tool.
Scoped creds · Full audit · SIEM streamNever locked in
The model is just a setting. Swap Claude for ChatGPT, Cursor, or whatever ships next, and your context, connections, and skills carry over to every surface without a rebuild.
Claude · ChatGPT · Cursor · CopilotSpend less
Context gets built once and reused on every call instead of rediscovered each time a query runs. Cost and latency keep dropping as the workspace grows and more of the work is already cached.
Build once · Reuse every queryMCP is the connection.
MarcoPolo is the workspace.
Each user or agent runs in a dedicated sandbox, hosted in your cloud and accessible from any AI surface. Credentials are scoped per user and never reach the model's context window.
Two outcomes for the same question.
“Which deals slipped last quarter and what engineering issues were blocking them?”
Native MCP hands the agent a connector.
AI needs a place to work.
01
Salesforce MCP returns 18 slipped deals into the context window.+25K tokensschema + records02
Jira MCP returns 64 engineering tickets into the context window.+30K tokensschema + tickets03Now join them. Where, exactly? The model string-matches account names against customer fields.+10K tokensmodel reasoning
No insights · just a partial list, and a retry. Every record now sits in the model's context.
Every system your team actually uses.
Cloud warehouses, databases, SaaS tools, and storage. All accessible through one governed interface.
Don't see your system? We're adding connectors weekly. Request one.
What AI leaders have built on MarcoPolo
Drawn from workflows our customers are running today.
Built with teams already scaling AI in production.
The MarcoPolo MCP layer is what's making the data actionable. CSMs with a new account don't have to ask anyone · the workspace already knows.
+ growingDon't just take our word for it. Ask your favorite AI.
Let ChatGPT, Claude, Gemini or Perplexity help. Click a button and see what your favorite AI says about MarcoPolo.
Enable AI to work with your enterprise data.
Start with a discovery call this week. From there, your security team reviews the architecture, and you're running a production pilot in your cloud within six weeks.
