Clari+ Salesloft has introduced new capabilities designed to deliver connected revenue intelligence across every layer of the sales process. One capability links forecasting and pipeline insights directly to seller execution, while the other—a new Model Context Protocol (MCP) Server—extends live revenue intelligence to any AI tool, enabling teams to uncover insights, take action, and scale more effectively.
As AI becomes more ubiquitous in GTM, strategy and execution remain split across systems, leaving a gap between insight and action where deals lose momentum and follow-through breaks down. At the same time, a key limitation is emerging: most tools still operate without access to the full context of pipeline activity, forecast signals, and deal progression that actually drives revenue decisions — leaving AI to operate on incomplete signals and generic assumptions rather than what’s really happening in the pipeline.
Clari + Salesloft is addressing that in two ways. First, the company has connected Clari’s forecasting and pipeline insights directly to Salesloft’s execution layer, allowing teams to act in the same workflows where issues are identified, rather than switching between disconnected systems. Additionally, it’s introducing a new MCP Server that lets AI tools like Claude, ChatGPT, Microsoft Copilot, Gemini, and Salesforce Agentforce operate on live Salesloft data. This includes pipeline movement, deal activity, and customer interactions that typically remain siloed or require manual exports — limiting the depth of analysis revenue teams can run and the custom AI experiences they can build.
“Clari built its reputation helping companies understand their revenue. Salesloft built its reputation helping teams execute on it,” said Steve Cox, Chief Executive Officer, Clari + Salesloft. “The gap between insight and action is often where deals stall or slip. This release is about closing that gap. Bringing action directly into the workflows where revenue decisions are made, and making that same data usable in the AI tools our customers rely on every day.”
“With the Salesloft/Clari integration, our reps are generating emails with AI and sending them without ever leaving Clari. No switching, no friction — just action, providing a more seamless workflow in one platform, “ said Andy Dorling, Sales Enablement Manager at GWI.
More AI Tools, Working From the Same Revenue Reality
This launch marks a fundamental shift in how revenue teams design and operate their go-to-market processes. Most teams are not short on ideas — they are short on the ability to execute those ideas across fragmented systems. That changes today.
“Most AI conversations in revenue are still about what the AI can see,” said Kylie Fuentes, Chief Product Officer, Clari + Salesloft. “We’re moving past that. By extending the intelligence and revenue context from Clari + Salesloft – like live pipeline signals, call data, and deal activity – into agentic workflows powered by any AI tool, you unlock the creativity of your teams. RevOps teams have always had the instincts. Now they have the surface area to match.”
With Clari + Salesloft’s MCP Server, best-in-class organizations can leverage proprietary signals and real-time pipeline context to move from insight to coordinated action in ways that were previously impossible. The compounding effect begins when signals do not just inform decisions — they trigger them.
Practical applications are immediate and powerful. Revenue teams can generate a structured implementation plan the moment a deal closes — automatically drawing buyer goals from call transcripts, initiating the appropriate Cadences, and assigning ownership to the right customer success managers. They can connect call sentiment with support ticket volume and active Cadences to trigger automated customer plays in real time. They can also unify engagement data with product usage and payment history to build a true customer health signal and surface risk earlier.
Once organizations discover how the MCP Server expands what their existing systems can actually accomplish, the limiting factor shifts from technology to imagination. Clari + Salesloft is building the foundation to bring that context together, so AI does not simply observe the business. It helps run it.
Connecting Revenue Strategy to Execution
Having strong visibility into the pipeline and forecast is only half the equation. The other half is speed — how quickly insight turns into action at the rep level. Revenue teams can identify risk in forecast reviews and capture next steps in calls, but getting that insight in front of reps at the right moment, in the right place, remains a challenge.
Clari + Salesloft is closing that gap by connecting Clari’s forecasting insights directly to Salesloft’s execution layer, allowing teams to act from the same workflows where issues are identified without switching between systems or losing momentum mid-deal.
This enables teams to:
- Act directly from Clari forecast and deal views.
Managers and reps can create Salesloft tasks and send AI follow-up emails directly from Clari Forecast and Clari Inspect, without leaving the workflow where issues are identified. - Convert call insights into action in one step.
Reps can turn AI-generated action items into tasks and follow-up emails directly from the Clari Copilot call recording experience, using the context already captured. - Extend execution into forecasting and pipeline workflows.
Salesloft sales engagement capabilities are now accessible alongside revenue workflows, reducing the need to switch between systems to act on pipeline insights.
The shift is toward making forecasting more operational, where insights drive action in real time, and those actions feed back into improving forecast accuracy over time.
“With this new integration, our reps are seeing significant time and energy savings by utilizing AI-generated follow-up emails after every customer call,” said Spencer Hercus, Associate Marketing Automation Manager at Lucid.
Learn more about the Predictive Revenue System
Related News:
SoftServe Report: Agentic AI Set to Transform Software Engineering
