After a call ends, there's always a list of things to do. Write the follow-up. Update the CRM. Check how the rep scored. AI Agents handle all of it for you, quietly running in the background while your team focuses on what they actually enjoy, talking to customers.
Set a goal. Choose a trigger. Done.
What is an AI Agent?
An AI Agent is an automated task runner inside Demodesk. You give it a goal (written as a prompt), tell it when to run, and it handles the rest on its own. No manual steps needed.
When can an agent run?
Trigger | What it means | Example |
Schedule | Runs at a fixed time | Every Monday at 9 am |
Meeting event | Runs when a meeting ends | After every sales call |
External (webhook) | Runs when an outside tool sends data to Demodesk | A form is submitted and needs to be routed |
What can an agent do?
Read meeting data
What it can do | Example use |
Pull up details about a specific meeting | Check who attended and when |
Search across past meetings | Find all calls with a specific customer |
Read AI-generated summaries | Use the summary to write a follow-up |
Read scorecard results | Check how a rep performed on a call |
See how much each person talked | Flag calls where the customer barely spoke |
Get meeting tags | Filter meetings by topic or outcome |
Work with CRM data
What it can do | Example use |
Search for contacts, deals, or companies | Find all open deals in a territory |
Read CRM data tied to a meeting | See what deal stage a call was linked to |
Get deal insights | Surface risks or next steps on a deal |
Communicate
What it can do | Example use |
Send a notification inside Demodesk | Alert a manager when a threshold is crossed |
Send an email | Automatically send a follow-up after a call |
Remember things
What it can do | Example use |
Store and retrieve information across runs | Remember a customer preference mentioned in a past call |
Manage Demodesk settings
What it can do | Example use |
Create or update other agents | Build an agent that manages other agents |
Manage scorecard templates | Update scoring criteria automatically |
Manage prompts/skills | Keep AI instructions up to date |
Connect to external tools
What it can do | Example use |
Call an external system via a Custom Integration | Push meeting outcome to your CRM after a call |
Real-world use cases
Use case | Trigger | What the agent does |
Weekly team digest | Every Monday morning | Searches last week's meetings, reads summaries, sends a team notification |
Auto follow-up email | Meeting ends | Reads summary and scorecard, sends a follow-up email to the customer |
CRM hygiene check | Meeting ends | Checks for missing CRM fields and flags them |
Coaching alert | Every day | Checks scorecard results, sends a notification if a rep scored below a threshold |
External system sync | External (CRM update) | Receives a signal from your CRM and pushes meeting data back into it |
Real-world examples
Real-world examples
Demodesk → Gainsight (without a native integration)
The situation
Your team uses Gainsight as your main CS tool. Every time a sales or CS call ends in Demodesk, you want an Opportunity to be automatically created in Gainsight — without anyone doing it manually and without needing a native integration between the two tools.
How the agent handles it
When a meeting ends, the agent runs automatically and does three things:
Step | What happens |
1 | Reads the meeting details and grabs the company name |
2 | Reads the AI summary of the call |
3 | Calls the Gainsight API directly and creates the Opportunity. Gainsight matches it to the right record automatically |
No middleware like Make.com needed.
What you need to set up (one time)
A Gainsight API key (your admin generates this in Gainsight settings)
That key added as a Custom Integration in Demodesk
A clear definition of what should trigger the Opportunity — e.g. every call, or only calls where strong buying intent was detected
What are Custom Integrations?
This is how agents talk to tools outside of Demodesk, for example, your CRM, internal database, or any tool with an API.
An admin sets up the connection once: they give it a name, add the API address, set which actions are allowed, and store the API key securely. After that, agents can use it automatically.
Rule | What it means |
Agents can only call allowed endpoints | Your admin decides what the agent is and isn't allowed to do |
API keys are stored encrypted | The agent uses them without ever exposing them |
How much does it cost?
Agents are billed across two separate meters.
1. Workflow Runs
Counted each time an agent executes.
Plan | Runs per month | Price |
Starter | 1,000 | Included with any plan |
Growth | 5,000 | €299 / month |
Scale | 25,000 | €999 / month |
Enterprise | Unlimited | Custom — contact us |
A 20-person team running 2 agents per user per day uses roughly 1,200 runs per month.
2. AI Compute Credits
Covers the AI processing each agent run uses.
Detail | How it works |
Free credit | €5 per user, one-time |
Top-ups | Any amount, any time — no minimums |
Pricing | Billed at cost + 10% platform fee |
Transparency | You can see exactly how many credits each run uses |
How do I create an agent?
The easiest way is by asking the AI Analyst directly in plain language.
For example: "Create an agent that runs every Monday and sends me a summary of last week's meetings."
The AI Analyst builds the agent for you, including the trigger and prompt. You can then review it, make changes, or enable it straight away.
After creating any agent
Action | When to use it |
Run now | Test the agent manually before waiting for the trigger |
Execution history | Check past runs and whether they completed successfully |
Edit agent | Update the prompt at any time without recreating the agent |
Enable / Disable toggle | Pause an agent without deleting it |