Same automation. Four different workflows.
Tuesday you saw the code. Today you see how analysts, managers, ops leads, and AI agents actually use it. Each role has different needs, different views, different wins.
Team Workflows
See how different roles use the same system to transform their daily work.Click each role below
Before Automation
With Automation
Workflow Process
Impact By The Numbers
"I finally get to do actual analysis instead of being a data entry clerk."
— Investment Analyst, 4 years CRE
How Roles Work Together on One Deal
Watch how all four roles collaborate on a single deal from pipeline entry to IC approval.
123 Main St, Class A Office, $45M acquisition
✨ Scroll here to watch the workflow
Practice-Wide Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| Deals Analyzed/Month | 15-20 deals | 60-80 deals | 4x throughput |
| Time to IC | 12-15 days avg | 3-5 days avg | 75% faster |
| Data Accuracy | ~85% (manual errors) | 99.8% (validated) | +14.8 pts |
| Team Capacity | 3 analysts, 1 manager | Same team, 4x output | No new hires |
Getting Your Team On Board
Analysts think AI will replace them
Show career path: 'You'll spend 88% less time on data entry, 88% more time on strategic analysis and deal sourcing.' Frame as promotion, not replacement.
Analysts see it as leveling up. Junior analysts do work that used to require seniors.
Managers don't trust AI assumptions
Run parallel for 30 days: AI analysis + manual analysis. Show 99.2% match rate on comps, AI catches risks humans missed 23% of the time.
Trust builds through data. Managers start asking AI questions before analysts.
Ops worried about upfront cost and integration
Calculate ROI: 308 hours saved/month × $75/hour blended rate = $23,100/month savings. 30-day payback even at $20K setup.
Show monthly savings chart. Math makes decision obvious. Integration takes 2 weeks, not 6 months.
Team resistant to changing Excel-based workflow
Don't force new tools. AI outputs to Excel/Google Sheets. Analysts work in familiar environment, just with pre-filled data.
Zero learning curve. Adoption happens in days, not months. Analysts customize their own templates.
Leadership worried about losing institutional knowledge
AI codifies best practices. Every deal analyzed using firm's methodology. New hires onboard 3x faster with consistent examples.
Institutional knowledge scales. Turnover no longer catastrophic. Firm gets smarter over time.
Investment & ROI
Typical payback in 30-45 days through time savings
Pricing
ROI Calculator
Proven Results
From Demo to Live in 3 Weeks
From demo to production in just 3 weeks
- Connect data sources (CoStar, Yardi, internal databases)
- Upload 10 sample deals for AI training
- Configure underwriting model templates
- Set up role-specific dashboards (analyst, manager, ops)
- Train analysts on AI-assisted workflow (3hr session)
- Train managers on review dashboard (2hr session)
- Train ops on pipeline reporting (1hr session)
- Run pilot with 5 live deals, gather feedback
- Adjust model assumptions and risk flags
- Roll out to all users, migrate active pipeline
- Daily check-ins for first week (15 min standups)
- Measure baseline: deals/week, time/deal, accuracy
- Compare to new performance after 7 days
Enterprise deployments with custom AI models may take 6-8 weeks. We'll run parallel with your existing process to minimize risk.
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