Scale agents across the enterprise—
without chaos.
Palma.ai operationalizes MCP so agents can access core systems consistently across teams: curated capabilities, standardized access, and enterprise-wide visibility.
From pilot to platform
How Palma.ai solves scaling
Standardize the capability layer
Palma.ai turns MCP into an enterprise standard: capabilities are published once and reused across agents, teams, and AI frameworks.
Curate tool access per use case
Agents become scalable when they get a focused set of building blocks. Palma.ai supports curated exposure so agents see what they need—nothing else.
Govern cross-boundary workflows
When an agent crosses departments (Sales → Finance, Support → Legal), Palma.ai provides consistent policy enforcement and audit.
Operate MCP like a platform
Health signals, usage, and performance across MCP servers and tools—so platform teams can run enterprise agent infrastructure with the same rigor as APIs.
The problem
Pilots work because the same few people sit in the same room. At scale, that breaks:
Tool sprawl: every team invents their own "agent integration"
No shared discovery: agents can't reliably find the right capabilities
Cross-boundary risk: agents touch systems owned by different departments
No operational view: failures and cost appear as "AI is flaky"
From chaos to clarity
One MCP layer for the whole enterprise
Each team builds custom integrations. No shared standards.
One Palma-governed MCP layer. Reusable across all teams.
What "good" looks like
A single MCP access layer in front of core systems
Reusable capabilities instead of one-off integrations
Consistent identity, policies, approvals for cross-team calls
Central observability across agents, tools, and workflows
Outcomes
Faster rollout from 1 team to many
Reduced rework and duplicated integrations
Safe cross-department automation
A stable foundation that survives new models, new agents, and new vendors
Turn agent pilots into a scalable enterprise capability.
Use Cases
What are you solving for?
Different problems, one platform. See how Palma.ai addresses your specific challenges.
Scaling Agents
Pilots work, but enterprise rollout breaks.
One MCP layer for the whole enterprise.
Cost of Agents
Token waste and tool-call loops spike costs.
Predictable cost per completed task.
Agent Reliability
Multi-hop drift and tool boundary failures.
Agents that finish work correctly.