Per-client AI that learns each brand. Cross-client intelligence.
More clients should mean more profit. Instead, it means more manual work, more hires, thinner margins.
2-4 hours per client, every week. Analyst time producing zero strategic value.
Clients ask 'What did we actually get?' Platform ROAS doesn't answer that. Without incrementality proof, retention suffers.
Every 3-5 new clients means another analyst. Headcount scales linearly, margins shrink.
What works for Client A could help Client B, but nobody connects those patterns. Portfolio intelligence untapped.
Each client gets individual AI. Your agency gets collective intelligence across all clients.
Per-Client Reporting
Per-Client Reporting
Auto-generates reports for every client, delivered to their preferred channel. Learns each client's KPIs and format.
Per-Client Attribution
Per-Client Attribution
Proves incrementality for every client. True ROAS, not platform-inflated numbers. The proof that retains accounts.
Per-Client Forecasting
Per-Client Forecasting
Revenue and ROAS forecasting that learns each client's patterns. Set realistic expectations, then beat them.
Cross-Client Memory
Cross-Client Memory
Perfect recall across every client conversation and decision. Plus anonymized cross-client pattern learning for your agency.
Agencies also benefit from Sam (scenario planning), Dana (unified data), and Olivia (creative intelligence) - meet all 7 agents
Every client makes the intelligence sharper for every other client. All data stays isolated and secure.
Seasonal trends working for Client A flagged as relevant for Client B. Your whole portfolio benefits.
New clients ramp faster. The system already knows what works in similar verticals from your portfolio.
Platform changes affecting multiple clients get one alert with impact across your book of business.
Seasonal patterns from 10 DTC brands produce more accurate forecasts than any single brand alone.
What changes when intelligence scales with your portfolio, not your headcount.
2-4 hrs per client per week. Manual data pulls.
Dex auto-generates per-client reports. 20-40 hrs/week saved.
Platform ROAS clients don't trust. Defensive QBRs.
Parker shows true incremental ROAS. Clients see real value.
Every 3-5 new clients = another analyst hire.
Add clients without headcount. Intelligence scales automatically.
Insights from Client A never reach Client B.
Maya surfaces anonymized patterns across your portfolio.
Guesswork on budgets. Overpromise, underdeliver.
Felix forecasts per client. Set expectations, then beat them.
Based on pilot programs with agencies managing 5-25 ecommerce clients.
Unified dashboard for all accounts. Each client gets individual AI that learns their brand, with cross-client intelligence identifying shared trends. Per-client auto-reports eliminate manual work.
Yes. Each client's data stays isolated, but the intelligence layer identifies anonymized patterns across your portfolio. Trends working for one client get flagged for similar clients.
2-4 hours per client per week. For a 10-client agency, that's 20-40 hours weekly freed up for strategy.
Parker's incrementality attribution gives agencies defensible ROI proof. Show clients true incremental revenue, not inflated platform numbers.
Agency tiers scale with client count. Per-client cost decreases as your portfolio grows. Contact us for details.
30-min demo with your agency data. Live.
