As AI moves into enterprise operations, Sweep is tackling a harder problem: helping agents understand the complexity already present in business systems.
Enterprise systems are complex because the real world is complex. Every automation, workflow, data model, and report reflects a decision the business needed at the time. The real challenge now is to make that complexity legible enough for both people and AI agents to act on it safely, keeping the valuable parts and dropping the rest.
Sweep, the agentic layer for enterprise systems, announced the launch of its cross-platform agent for Salesforce, Snowflake, and Data 360. The new capability allows teams to reason across all three systems simultaneously through a continuously updated dependency graph, so they can see how enterprise data, workflows, metadata, permissions, and business logic connect before making any change.
Generic AI was built for clean, greenfield environments. But Enterprise AI has to work inside real systems that carry years of complexity, which often require first-hand context to understand and build upon.
The gaps between systems, particularly, are where complexity compounds, explains Sweep CEO and co-founder, Ido Gaver.
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“Every platform wants to be the agentic layer for its own domain. None of them can see what happens in between,” says Gaver. “Enterprise system complexity grows with the business. Sweep gives teams a way to embrace that complexity, apply context, and use AI to discover, design, build, and monitor change across the systems that actually run the enterprise.”
When agents act with incomplete context, ordinary business logic can become operational risk. For example, an agent might approve an expedited order because they can see the customer record in Salesforce, but miss a credit hold stored downstream or a data-quality exception surfaced in Snowflake. Another team might change a picklist or workflow in Salesforce without seeing how that value feeds a Data 360 audience, a Snowflake report, or a downstream compliance process. In both cases, the issue is not the agent’s reasoning ability. It is the absence of cross-system context.
Sweep addresses that problem by making the connected stack understandable to both teams and agents. Instead of stitching together one-off queries, data catalogs, and platform-specific copilots, Sweep creates and maintains a live map of dependencies across Salesforce, Snowflake, and Data 360. Teams can ask plain-language questions, understand impact, and govern changes before they ship.
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How Sweep’s Cross-platform Agent Works
- Discover: Sweep automatically indexes metadata, schema, permissions, automations, and dependencies across connected platforms, creating a shared map of how revenue and data infrastructure actually operate.
- Design: Teams can use natural language to then ask cross-platform questions before making a change, such as which reports, data products, automations, audiences, or processes depend on a field, object, workflow, or dataset.
- Build: Sweep supports governed execution in Salesforce, where teams can turn approved plans into changes while preserving the context and impact analysis behind them.
- Monitor: Agentic Governance continuously scans connected systems for drift, permission inconsistencies, policy violations, and dependency risks, providing teams with a single source of truth across a distributed architecture.
Sweep’s internal benchmarks, derived from analysis of more than 12,000 anonymized chats between their customers and agents, show that what typically takes enterprise teams 11 hours of cross-system investigation is compressed to roughly 1 hour. That’s because dependencies are already mapped and traced, and the downstream impact is already visible before the change ships.