bedda.ai Spotlight: Hand Work to AI Agents, Get Approval Cards
Feature spotlight: Multiplayer agents
Every week we highlight one bedda.ai feature. This week: multiplayer agents — the ability to assign work to AI using plain language and get approval cards for every decision the agent can't make alone.
The automation dilemma
Most automation is binary: you set up a rule, and the system follows it. But the moment you need judgment — a decision that depends on context, or where you want final say — you're locked out. The system can't surface questions; it either decides (and you hope it's right) or doesn't automate at all.
bedda.ai agents solve this by putting humans in the loop where it matters.
How agent handoff works
You assign work to a bedda.ai agent in plain English:
"Review these support tickets and categorize them: high-priority (urgent customer issue), medium (feature request with demand), low (one-off question)."
The agent:
- Reads your data — every ticket, with full context
- Applies judgment — categorizes based on what makes sense
- Raises approval cards — surfaces edge cases and judgment calls
- Waits for you — your answer unblocks it
Example:
Agent: "I've categorized 47 tickets. But ticket #1392 is ambiguous — it's a feature request (normally medium priority) but from your top customer (would be high). Approve as high, or stay with medium?"
You tap "high" — and the agent records your call and continues.
Cards are first-class
Approval cards aren't notifications — they're recorded work. They persist:
- Durable — reload, and your approval is still there
- Auditable — every decision is logged
- Retriable — agent continues from where it left off, with your answer in hand
- Reversible — change your mind, and the agent can redo the work
This is why they matter for teams: decisions are explicit, not hidden in logs.
Where it shines
Refund processing: Agent reviews transaction and customer history, identifies a $X refund request, surfaces "Approve this refund?" You tap yes or no.
Content moderation: Agent flags comments that might violate policy, surfaces each as a card: "Remove this comment for [reason]?" You review the context and decide.
Data quality: Agent scans your database for inconsistencies, raises cards: "This record has no email. Delete or mark for manual review?" You choose.
Customer escalation: Agent reads a support ticket and your internal rules, decides it needs human review, surfaces a card: "Escalate to support team?" You approve.
In each case, the agent handles the work. You handle the judgment. Real multiplayer.
Try it
Open bedda.ai and assign a task to an agent. Describe it in plain English. Watch the approval cards appear.
This is part of the bedda.ai Feature Spotlight series. We publish a new feature every week.