Proshort wins enterprise adoption with RateGain for its AI-native revenue platform

For years, revenue teams have been surrounded by data but starved of clarity. Calls are logged, notes are taken, dashboards glow green, but deals still slip, forecasts wobble, and coaching remains reactive. Proshort was founded to fix that gap. Built as an AI-native revenue intelligence and “Supercoaching” platform, the company is betting that the next generation of revenue operations won’t be about better reporting, but about real-time execution intelligence embedded directly into how teams sell.This thesis has now received strong enterprise validation.

On March 10, 2026, Proshort announced that RateGain Travel Technologies Limited, a global SaaS leader in travel and hospitality, has selected Proshort’s AI-native revenue platform for its global sales organization. The platform will be deployed to improve forecasting accuracy, strengthen pipeline visibility, and bring greater execution consistency across teams. The engagement marks a significant step in Proshort’s expansion into large, complex enterprise environments.

From reporting tools to systems of intelligence

Founded with the belief that revenue operations had become an administrative layer rather than an execution engine, Proshort set out to rethink the category from first principles.

CEO and Founder Gaurav Mishra traces the origin of the company to a pattern he saw repeatedly across sales teams.

“Reps were doing the work of selling, but the system was working against them,” he said. “After every call, critical context lived in someone’s head, messy notes, or Slack threads, while the CRM stayed stale and dashboards stayed optimistic.”

This disconnect also crippled coaching. Managers were expected to guide reps and improve outcomes, yet had little visibility into what actually happened inside customer conversations. Despite an abundance of tools, organizations lacked shared knowledge.

“Great conversations lost momentum because the organization couldn’t capture and reuse context in real time,” Mishra said. “RevOps became a reporting layer. It should be the operating system for execution.”

Proshort was designed to be that operating system.

Why AI-native architecture matters

While many revenue tools are now adding AI features, Proshort took a different path. Instead of layering AI on top of legacy systems built for manual data entry, the company poses AI to be the primary user from day one.

“That changes the architecture,” Mishra explained. “Revenue context isn’t a table; it’s a network of people, accounts, objections, competitors, and outcomes.” At the core of Proshort’s platform is its proprietary Context Graph, which connects customer conversations, deal activity, and market signals into a unified, continuously updated intelligence layer. Autonomous AI agents analyze deal progression, surface risks, recommend next steps, update CRM records, and deliver personalized coaching — all while learning from outcomes.

“The goal isn’t insights, it’s execution,” Mishra said. “Agents turn intelligence into action.”

This approach also allows Proshort to identify coaching opportunities automatically, highlighting where reps struggle with objections, positioning or stakeholder engagement, and enabling managers to intervene earlier.

The RateGain partnership: enterprise validation

For Proshort, the partnership with RateGain represents more than a new customer win. It signals readiness for enterprise-grade scale and complexity.

RateGain, founded in 2004 and headquartered in India, is a global provider of AI-powered SaaS solutions for travel and hospitality. The company serves over 13,000 customers and 700 partners across more than 160 countries, working with 33 of the world’s top 40 hotel chains, four of the top five airlines, and all leading online travel agencies and metasearch platforms.

At this scale, revenue execution challenges are amplified.

“AI is redefining the foundation of modern vertical SaaS companies,” said Bhanu Chopra, Founder and Managing Director of RateGain. “AI-native revenue platforms will help organizations operate with greater intelligence, predictability, and speed.”

Chopra added that the partnership would strengthen forecasting and pipeline visibility, improve execution consistency, and help teams act faster on customer needs at scale.

From a finance and planning perspective, the value is equally clear.

“Predictability and real-time visibility into revenue are critical for RateGain’s strategic planning and long-term growth,” said Rohan Mittal, CFO, RateGain.

“Proshort’s AI-native platform strengthens our ability to monitor pipeline health, improve forecast accuracy, and drive more efficient execution across our global revenue organisation.”

For Proshort, the collaboration confirms that its platform can meet enterprise requirements around security, compliance, cross-region workflows, and role-based adoption — areas where many AI sales tools struggle.

From systems of record to systems of execution

When teams rely solely on dashboards, reality lags updates, nuance is compressed into stages, forecasts become confident guesses, and coaching lacks behavioral signals. Managers, in particular, face a blind spot: they’re responsible for improving performance, but rarely see how deals actually progressed or where conversations went off track.

Proshort adds a live execution layer, showing what changed since the last call, what risks are emerging, and what actions matter next — grounded in real interactions rather than static fields.

Human judgment still closes deals

Despite its deep use of autonomous agents, Proshort is careful not to overstate AI’s role.

“Deals will still be closed by people,” Mishra said. “AI should handle what humans struggle with at scale: capturing context, spotting patterns, remembering every change, automating operational work.”

The founder believes that Humans should retain ownership of strategy, trust-building, negotiation, ethics and judgment in ambiguity. In Proshort’s design philosophy, AI proposes and humans decide, while preserving context so execution continuously improves.

What “Supercoaching” looks like in practice

One of Proshort’s defining concepts is Supercoaching, which Mishra describes as a fundamental departure from traditional sales enablement.

“Supercoaching is daily, contextual, and measurable; not quarterly training,” he said.

For revenue leaders, that means visibility into which deals shifted and why, identifying top risks per rep based on real calls, tracking recurring objections, and accessing precise coaching snippets from top performers. The system also generates focused weekly action plans grounded in live deal data.

“Traditional enablement is content plus hope,” Mishra said. “Supercoaching is signals, interventions, and proof.”

Measuring ROI in real terms

Customers measure Proshort’s impact across three areas: execution efficiency, deal outcomes, and predictability.

Teams report reduced administrative burden, cleaner CRM data, faster follow-ups, improved win rates, reduced deal slippage, and more accurate forecasts with earlier risk detection. Many also see a step change in coaching quality as managers gain direct visibility into customer interactions instead of relying on second-hand updates.

“What stands out most is speed and clarity,” Mishra said. “Leaders see risk earlier, reps are better prepared, and RevOps spends less time stitching tools together.”

Where revenue tech is headed

Looking ahead, Mishra believes revenue technology will shift decisively from systems of record to systems of execution.

“We’ll move from dashboards to always-on copilots and autonomous agents,” he said. He expects specialized agents to emerge for deal execution, competitor tracking, pricing, stakeholder mapping, and coaching.

However, he cautions that flashy AI won’t determine winners.

“They’ll win on trusted context, reliable actionability, governance, and deep workflow integration,” he said.

That is also Proshort’s long-term moat. While features can be copied, accumulated context, feedback loops tied to outcomes, and enterprise-grade governance are far harder to replicate.

Building trust in the AI era

As an AI-era founder selling to large enterprises, Mishra said three lessons stand out: trust matters more than timing, focus drives adoption, and enterprises buy outcomes, not AI.

“Reduce slippage, improve forecasts, scale coaching — AI becomes the mechanism, not the pitch,” he said.

With RateGain now onboard, Proshort appears well-positioned to test that philosophy at global scale — and to help redefine how modern revenue teams operate in an AI-first world.