Not a chatbot. Not an assistant. A workforce.
Eight specialized AI teammates, each with a defined role and scope. They review connected location data and prepare or execute bounded next steps under your workflow rules.
Monitors and agents. Different functions. Same goal.
Watches everything. Flags what matters.
Monitor-class AI teammates review operational execution across connected locations using the checks you configure.
- ✓Alerts for configured execution gaps
- ✓Consistent review across connected locations
- ✓Less manual audit work
Decides. Acts. Reports.
Agentic-class AI teammates detect problems and can carry out bounded actions within configured guardrails.
- ✓Bounded task execution
- ✓Human approval where the workflow requires it
- ✓Uses configured, approved operating patterns
A team of specialists for multi-location operations.
Blendy
Platform Agent
The face of the workforce. Answers questions on live location data, writes coaching briefs, and composes communications with your business context built in.
Revenue Recovery Specialist
Watches billing health across the network, finds failed payments and revenue at risk, and prepares recovery priorities.
Sales Pipeline Specialist
Manages the pipeline from lead to conversion. Tracks visits, flags stuck leads, recommends the next best action.
Campaign Performance Agent
Monitors marketing performance across the network and flags locations falling below benchmark.
Class Utilization Optimizer
Analyzes attendance, waitlists, and schedules to identify overcapacity and underfilled sessions.
Coaching Prep Agent
Builds daily coaching priorities for field teams using configured peer groups.
Customer Lifecycle Manager
Tracks available customer-lifecycle signals, flags retention risk, and prepares win-back actions.
Data Integrity Agent
Audits data from connected systems and flags integrity problems before other workflows use it.
Answers with receipts. Actions with approval.
Blendy shows where an answer came from, how fresh it is, who's allowed to see it, and what to do next. Each action follows the approval rule configured for its workflow.
Blendy
In this sample day, 3 of 42 locations missed the 24-hour follow-up window. Westside: 6 of 14 new leads not contacted. River North: 4 of 9. Midtown: 2 of 11. The biggest gap is Westside, where both closers were off.
- Sources & freshness
- Lead Engine · MMS lead feed + call and text logs · fictional sample snapshot
- Scope
- Showing all locations. You're signed in with a regional role.
Suggested next action
Draft follow-up assignments for the 12 missed leads and notify each location manager?
Audit trail · Approved actions are logged with who approved, when, and the data behind them.
Blendy
In this sample week, 23 members across 5 locations show risk signals: 14 with unresolved failed payments, 6 whose visit frequency dropped more than 50% in 30 days, and 3 with both. Estimated revenue at risk: $2,840 per month.
- Sources & freshness
- Rev Engine + Engagement Engine (early access) · fictional billing + check-in snapshot
- Scope
- Showing all locations. You're signed in with a regional role.
Suggested next action
Queue billing recovery for the 14 payment issues and win-back outreach for the 6 low-visit members?
Audit trail · Sent messages are attributed and timestamped. Queued messages can be reviewed or canceled before send.
Blendy
The fictional June 2026 lead campaign produced 212 leads, 38 joins, and $19,400 in first-90-day revenue. Join rate was 34% higher than the May 2026 sample. Six locations received leads but converted below 10%; the pattern points to follow-up speed, not lead quality.
- Sources & freshness
- Lead Engine · fictional ad-spend + MMS join snapshot, matched person by person
- Scope
- Showing brand-wide results. Location managers see only their own.
Suggested next action
Flag the six slow-converting locations for the next coaching briefs?
Audit trail · Flags appear in each brief with the data that triggered them.
Blendy
Seven commitments were captured from the fictional July 8, 2026 franchise call. Four are complete, two are on track, and one is overdue: the pricing one-pager owed to franchisees, due July 10, 2026, owner S. Keller. It is marked escalated.
- Sources & freshness
- Blend Synapse meeting capture · fictional Work Management (beta) snapshot
- Scope
- Showing items you're allowed to see. Commitment owners see their own detail.
Suggested next action
Send the owner a reminder with the meeting excerpt attached?
Audit trail · The reminder, the excerpt, and the escalation history stay on the record.
What happens before your team finishes their coffee.
This sample morning shows how the AI Workforce can find exceptions and turn them into accountable next steps.
AI prepares the action. Your rules determine what happens next.
Each action follows configured review, approval, and audit rules. Customer communications can be held for human approval.
Recommend
AI teammate identifies the action and provides full context.
Review
Manager sees reasoning, data, and expected outcome.
Approve
A manager approves or edits actions that require approval.
Execute
Once authorized, AI carries out the action and logs the result.
Learn about our privacy approach: See our full data privacy approach
See the AI Workforce in action.
Use a 30-minute Fit Review to see which teammates match your workflows, data, and approval requirements.