Sell more with the same team
Your sales team still spends more time on CRM, reports and proposals than actually selling. AI eliminates the operational burden and frees reps for what drives revenue: relationships and closing.








Revenue grows, headcount doesn't
+40% sales productivity in the first quarter
Sales analysis that took 15 days became daily, with automatic insights per rep. Forecast vs. actual in real time, not in a biweekly meeting.
Same team, double the capacity
Your sales team focused on selling, not filling CRM, building proposals or consolidating reports. AI handles operations, reps handle relationships.
From biweekly cycles to daily decisions
Pipeline data, individual performance and forecast consolidated automatically. Sales managers with full visibility without waiting for period close.
How sales teams use OORT
Forecast vs. actual by rep, by product, by region. Automatic comparison with deviation insights. What took a biweekly meeting is now a daily dashboard.

How sales teams use OORT

Diagnosis, automation and control for your sales team.
Every stage of the cycle connected to results.

AI Assessment
Agents interview your teams, map real processes and project the return of each opportunity. The result is a complete diagnosis with detailed reports, a prioritization roadmap and a clear AI adoption plan. Can be contracted separately.
Discover Assessment
AI-First Data
Data from CRM, ERP and sales tools organized and governed where they already are. Client history, pipeline and performance accessible to generate real-time insights.
Discover AI-First Data
OORT Flows
Lead qualification, proposal assembly, automatic follow-ups and consolidated performance reports. Sales cycle running 24/7 with governance.
Discover Flows
OORT Culture
Reps and managers prepared to use AI in their sales routine. Hands-on training integrated with the CRM and tools your team already uses.
Discover CultureEnterprise security for your operation
Your data never leaves your environment. Encryption at every layer, granular access control, full audit trail and LGPD compliance by default.
Frequently asked questions about AI for Sales
+40% productivity in the first quarter, with sales analyses that previously took 15 days becoming daily. AI automates CRM, builds proposals and consolidates reports, freeing reps for relationships. According to McKinsey (2025), companies that implement AI in sales increase conversion rates by up to 50% and reduce the sales cycle by 30%, with the biggest impact coming from intelligent lead qualification.
Forecasting shifts from manager gut feeling to real pipeline data, seasonality and conversion history. Projections are updated daily with significantly higher accuracy than manual methods. According to Gartner (2025), organizations using AI for sales forecasting achieve 85% prediction accuracy, compared to 55% with traditional methods, reducing revenue planning errors by 40%.
It complements. AI handles operational tasks — CRM entry, proposal assembly, report consolidation and initial lead qualification — freeing the rep for what drives revenue: relationships, negotiation and closing. With the same team, capacity doubles. According to Forrester (2025), sales teams that adopt AI report 35% more time on high-value activities and a 28% increase in close rate.
AI agents analyze interaction history, company profile, digital behavior and ICP fit to automatically score and prioritize leads. The sales team receives a ranked list of opportunities with the highest conversion probability. According to IBM (2025), companies using AI for lead qualification reduce time spent on low-conversion opportunities by 60% and increase pipeline efficiency by 45%.
The first AI agents go live in weeks, not months. The Assessment maps the complete sales cycle — prospecting, qualification, proposal, negotiation and post-sale — and identifies the processes with the highest ROI for immediate automation. According to Deloitte (2025), incremental AI implementations in sales achieve payback in 3 to 5 months and are 3x more likely to succeed than large-scale projects.


