Forlena is rewiring the revenue motion. Here's what changed.
No signal on what needs attention. Scan the pipeline, decide where to start.
Walk in knowing exactly which deals need attention and why. AI prioritizes before you open your laptop.
Stage completion is the only metric. No way to know if a deal is actually healthy.
Evidence-based score across 6 dimensions. Updated on every activity, email, and stakeholder change.
Next steps live in the rep's head, scattered across notes and email threads.
System generates specific actions based on deal gaps. Rep reviews, approves, modifies, or dismisses.
Team screens manually. Hard to calibrate without a consistent signal at volume.
ICP-matched scoring from first contact. Learns from every closed deal. Gets sharper over time.
Email stays in the inbox. Logging it takes extra effort, so most of it never makes it in.
Auto-synced. Every email analyzed for sentiment, buying signals, competitor mentions, and new stakeholders.
Stakeholder picture lives across notes, emails, and memory — no single view.
AI maps every role. Flags missing decision makers before they become the reason you lose.
Stage × deal size, adjusted by feel. Everyone knows the number isn't reliable.
Win probability from evidence: deal score, stakeholder coverage, activity recency, and historical patterns.
Performance reviews once or twice a year, based on what the manager remembers.
On-demand. Based on your actual deal patterns. In your language. Personalized to where you lose.
A post-mortem if time allows. Rarely tied back to patterns across the team.
AI post-mortem: where it broke, what the timeline shows, what the stakeholder map reveals, what to change.
Weeks of implementation. Most teams go live on defaults and never revisit.
9 questions. 2 minutes. Calibrated to how you sell — stage types, scoring weights, ICP, thresholds, all of it.
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