MortgageFlow.
Built for the relationship.
A small brokerage wanted its own CRM. MortgageFlow is being built around private client relationships, mortgage opportunities and the follow-ups that keep those relationships moving.
Try Mira in the workspace ↓- Team
- Brokerage admin, brokers and assigned assistants
- Build
- CRM, pipeline, documents, follow-ups and AI assistance
- Current stage
- Code and local testing · live provider delivery unverified
See who needs a follow-up.
Ask about a renewal. Open the source record. Approve a reminder. See what Mira prepares and where the broker decides.
Who needs a call today?
Mira brings overdue follow-ups and unanswered messages into the broker’s morning briefing. The broker chooses the next conversation.
Where does each file stand?
Each mortgage sits at its current stage with a next action on the card. A broker can pick up a file and see exactly where to continue.
Ask about your book.
Find the client behind a renewal and prepare your next call.
One client in your book has a mortgage maturing in the next six months. Isaac Example’s refinance matures December 19.
Keep the relationship
with the broker.
Each broker needs a private book. The admin needs brokerage-wide oversight and shared policies. The build keeps those responsibilities distinct.
A maturity date can create a reminder. Mira helps the broker see who needs attention and prepare a follow-up, with the broker making the decision.
What is implemented in the build?
Private broker workspaces, contacts, mortgage opportunities, tasks, notes, document checklists and reports. Mira supports briefings, contextual questions and proposals for review.
What does AI do?
Mira helps surface relevant client context and prepare suggestions, drafts and tasks. Date-based reminders, sending checks and workflow schedules are ordinary software rules. The broker provides mortgage advice and controls approvals.
What still needs verification?
Real deployment, live email and SMS provider setup, hosting decisions and legal review remain part of getting the product ready for real users. The examples here use fictional data.