Tripled advisors. Same ops team.
Scaling from 1,500 to 5,000 advisors. Broker-dealer transitions automated end-to-end.
Why Caddi
Confidently roll out AI with
central governance and guardrails.
Adoption from the bottom up, control from the top down. Your team just shows the Caddi agent a task on a screen share and it’s automated. It’s the rare tool ops teams reach for every week, and the one place leadership sees, governs, and trusts every agent.
Firm automationLeadership view
24automations live
6teams building
100%runs logged
- Broker-dealer transitionsOperations1,240 runsRunning
- Matter intake & conflict checksLegal1,000+ / moRunning
- DocuSign filingCompliance3× dailyLive
- Vendor invoice follow-upsFinancenew loopNeeds review
- Client onboarding packetsAdvisorydailyScheduled
The AI mandate
Shadow AI, or AI you can audit.
Leadership told the firm to use AI. The only question is whether it happens in the shadows, or somewhere you control.
Without governance
Shadow AI
- Tools no one approved, holding client data.
- Automations built in silos that break silently.
- No record of what ran, or what it touched.
- Nothing you could put in front of a regulator.
With Caddi
Governed AI
- Every automation lives in one place.
- Every run is logged, with a full audit trail.
- Leadership sees who built what, and what it touches.
- Gate it, pause it, or let it run. Your call.
Why it worksBuilding it is easy.
Building it is easy.
Keeping it running is the job.
The demo is the easy part. Caddi is built for the months after: runs that hold, improvements you sign off on, and a bill that never surprises you.
Reliability
Runs hallucination-free, 24/7.
Caddi runs on a hybrid engine: deterministic code for the steps that can’t vary, AI only where judgment actually helps. You get the flexibility of AI with the repeatability of software.
Pure LLM agents nail the demo, then quietly drift by Friday.
Every run is unattended, error-handled, and logged, start to finish.
Maintenance
It improves after runs, not during them.
Non-deterministic AI has no business changing course mid-task. Caddi watches each loop, and once a run finishes it flags what broke or drifted and proposes a fix. You approve the change to the process; the AI never makes that call on its own in the flow of real work.
DIY agents improvise mid-run, and no one can say why the output changed.
Improvements land as reviewed changes you approve, never mid-run surprises.
Cost
No runaway token bills.
Because the deterministic core does most of the work, you’re not paying an LLM to re-reason every step of every run. One firm, one predictable price.
A partner burns $10k a month on agents that break by Q2.
One predictable price, with no token meter running in the background.
The payoff
Proven ROI in a week,
then it compounds.
Your first loop goes live in hours, and each one that ships exposes the next bottleneck worth clearing.
Step 01
The ROI you can name
The painful work you can already point to. Live in hours.
1,000+ matters automated a month.
Scaled case throughput across four workflows. Stopped hiring APEX developers.
Step 02
The ROI you couldn’t see
Surfaced during implementation. The lift compounds.
