How to Use Recall AI for Agents workflows

Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet, Microsoft Teams, and more. Get this data with our Meeting Bot API, Desktop Recording SDK, or Confirm live details on recall.ai before production use.

Practical Agents workflows examples

Example 1

Scenario:
Recall AI — Agents workflows (pass 1). Context: Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet, Microsoft Te

Objective:
Deliver a reviewable agents workflows result using Recall AI.

Inputs:
- Verified facts from recall.ai
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: API, Automation, Agents

Workflow:
Open Recall AI → Configure for agents workflows → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Recall AI capabilities; do not invent features.
- Confirm live details on recall.ai before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete agents workflows artifact plus a short verification checklist.

Example 2

Scenario:
Recall AI — Agents workflows (pass 2). Context: Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet, Microsoft Te

Objective:
Deliver a reviewable agents workflows result using Recall AI.

Inputs:
- Verified facts from recall.ai
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: API, Automation, Agents

Workflow:
Open Recall AI → Configure for agents workflows → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Recall AI capabilities; do not invent features.
- Confirm live details on recall.ai before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete agents workflows artifact plus a short verification checklist.

Example 3

Scenario:
Recall AI — Agents workflows (pass 3). Context: Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet, Microsoft Te

Objective:
Deliver a reviewable agents workflows result using Recall AI.

Inputs:
- Verified facts from recall.ai
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: API, Automation, Agents

Workflow:
Open Recall AI → Configure for agents workflows → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Recall AI capabilities; do not invent features.
- Confirm live details on recall.ai before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete agents workflows artifact plus a short verification checklist.

Example 4

Scenario:
Recall AI — Agents workflows (pass 4). Context: Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet, Microsoft Te

Objective:
Deliver a reviewable agents workflows result using Recall AI.

Inputs:
- Verified facts from recall.ai
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: API, Automation, Agents

Workflow:
Open Recall AI → Configure for agents workflows → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Recall AI capabilities; do not invent features.
- Confirm live details on recall.ai before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete agents workflows artifact plus a short verification checklist.

Example 5

Scenario:
Recall AI — Agents workflows (pass 5). Context: Recall.ai provides an API to get recordings, transcripts and metadata from video conferencing platforms like Zoom, Google Meet, Microsoft Te

Objective:
Deliver a reviewable agents workflows result using Recall AI.

Inputs:
- Verified facts from recall.ai
- Audience, channel, or technical constraints
- Success criteria and forbidden claims
- Relevant product surfaces: API, Automation, Agents

Workflow:
Open Recall AI → Configure for agents workflows → Pilot with sample inputs → Review against success criteria → Iterate one axis → Finalize

Requirements:
- Use only verified Recall AI capabilities; do not invent features.
- Confirm live details on recall.ai before promising volume or pricing.
- Human-review before external publish, send, billing, or compliance use.

Expected output:
A concrete agents workflows artifact plus a short verification checklist.

Checklist before you ship

• Confirm the workflow stays inside verified Recall AI capabilities
• Review outputs against recall.ai when accuracy or pricing claims matter
• Keep a short verification list for any claim you would publish externally