Over the last few years, a wave of “AI-native Gong alternatives” has arrived—tools like Sybill, Oliv, Momentum, and others.
The typical pitch:
“We’re just like Gong, but cheaper, faster, and more AI-driven.”
If you’re comparing these tools, the real question is:
Do you need a cheaper conversation recorder, or a different architecture that treats your sales data as a living knowledge system?
Gong: The Established Leader
Gong gives you:
Proven call recording and transcription at scale.
Revenue and pipeline intelligence based on conversation data.
Manager dashboards and coaching capabilities.
A mature ecosystem and brand trust.
It’s the obvious default in many enterprise RFPs.
The New AI-Native Crowd
Newer tools (Sybill, Oliv, Momentum, etc.) typically emphasize:
Lower cost and easier onboarding.
More automation around summaries, follow-up drafts, and CRM updates.
Tighter focus on AI workflows (e.g., follow-up generation, sequence triggers, notifications).
Modern UX and a faster product iteration pace.
They’re attractive if you like the Gong concept but want something more nimble.
The Shared Limitation: Still Transcript-Centric
Despite their differences, most of these tools still treat transcripts as the main asset:
Calls are analyzed, tagged, and summarized.
Insights are surfaced via dashboards, notifications, or AI chat.
CRM updates are made—but often as flat fields, not part of a deeper model.
What’s often missing is:
A persistent knowledge graph of deals, personas, objections, and collateral.
A clear view of skill development for each rep over time.
Consistent pre-call guidance and in-call help, not just post-call analysis.
A unified layer that connects CI, enablement, and forecasting.
That’s where the architecture matters more than “how much AI” you add on top.
Proshort’s Different Bet: A Conversation Graph, Not Just CI
Proshort is built around the idea that:
Sales conversations are a time-series dataset that should power prep, coaching, and forecasting in one place.
Practically, that means:
Each interaction (call, email, note) becomes a node in a conversation graph tied to a deal and account.
Objections, competitors, decision makers, and timelines are entities, not just text—so they’re trackable across the entire customer journey.
Reps get a Cursor-for-Sales experience: they can ask anything about a deal, a prospect, or a pattern across calls and get grounded, time-aware responses.
Managers see rep skills and behaviors evolve month-over-month, not just call counts and win rates.
Instead of aiming to be “Gong but cheaper,” Proshort aims to be:
The operating layer where calls, CRM, and enablement content all meet in one graph—and where AI agents can actually act on that structure.
Where This Leaves You
When you evaluate Gong vs newer AI tools vs Proshort, try asking:
Do we just want nice summaries and cheaper licenses?
Or do we want a system that learns from every call and turns that into:
Better prep
Smarter coaching
Cleaner forecasts
And a compounding enablement asset?
If it’s the latter, look beyond “Gong vs X” and toward platforms that treat your sales data as a long-term knowledge advantage—exactly where Proshort is focused.
