Attention alternative for revenue teams
Attention captures actions, Fluint traces them to revenue.
Attention gives you AI agents that take actions based on your sales calls. Fluint trains a private AI model to let you build any agent, with context engineered from your actual revenue outcomes.
A context layer that learns from your best deals.
Attention logs agent actions with an activity history. That's a good start. But remembering what happened is not the same as learning what predicts wins, and an audit trail is not the same as revenue attribution.
AI-trained predictors, not conversation-based patterns.
Attention "keeps getting smarter" by aggregating conversations. Fluint trains gradient-boosted and regression models on your actual closed-won outcomes, surfacing predictors like "CFO attended = 3.2× close rate" with statistical significance.
Revenue attribution, not just an action audit trail.
Attention shows you what their agents did. That's accountability. But it doesn't answer the question your CRO is asking: what revenue did that action create? Fluint traces every action to the deal outcome — closed-won, ACV, cycle time — so you know what your AI actually earns.
Your own private AI model, not a shared LLM fed by transcripts.
Attention feeds your conversations into generic frontier models. Fluint deploys a dedicated LLM per customer with private weights. Loaded with your GTM data, enriched by ML trained on your outcomes.
We have a bunch of tools, but none of them have had a bigger impact on our GTM efforts than Fluint. And it's not even close.
The best part here is how much faster our deals are closing when you consider that there are more stakeholders involved than we've ever experienced.
Matt G.
CRO of Sales Assembly
Comparison table
Fluint vs Attention: smarter than a fleet of agents
Sales signal capture & automation
Captures sales activity across calls, meetings, email, and CRM
Automatically updates CRM fields and activity logs
Generates AI-written follow-up emails after sales interactions
Summarizes sales conversations and key moments
Deal execution & pipeline intelligence
Executes follow-ups and next steps across the deal automatically
Detects pipeline risk based on full deal activity, not just calls
Flags stalled deals before they impact pipeline & forecasts
AI agent complexity & admin
Uses a fleet of task-specific AI agents that must be configured
One AI agent: Olli
Uses one AI agent with full deal and pipeline context
Allows reps and leaders to ask one AI and get action taken
Let’s see if there’s a good fit
We’ll look at how other GTM teams are already:
Engaging exec-level buyers
Engaging exec-level buyers with a strong point of view.
Driving 10.4X sales velocity
Driving 10.4X sales velocity with more calm, less chaos.
Confidently forecasting
Confidently forecasting, with deal reviews based on written evidence.
Enabling champions
Enabling champions to multithreaded and sell internally.
Are you a Sales Rep or AE?
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