A sales pipeline watcher in Teams + Dynamics 365
VYRA reads your CRM, drafts the deal brief when the stage advances, and pings the AE in Teams with the recommended next action: before the deal goes cold.
The work that needs an owner
AEs work the deals they see this morning. The deals that need a follow-up Wednesday get forgotten. Sales managers run pipeline reviews on Friday with stale data. Deals slip not because the team is bad but because the pipeline-watching part of the work does not fit in a calendar.
This route fits when
VPs of Sales, RevOps leads, and AE managers running mid-market and enterprise pipelines in Microsoft Dynamics 365 or Salesforce, with the team in Microsoft Teams. Especially useful for teams with 50+ active opportunities and AE/CSM headcount under 30.
What gets finished each week
- · Reads CRM activity for every active opportunity: stage changes, last contact, next step due
- · Drafts the deal brief when a stage advances or quota slips off track
- · Pings the AE in Teams with the brief and a recommended next action
- · Posts a Monday morning pipeline summary in the revops channel: deals at risk, deals stalled, deals worth pushing
- · Drafts follow-up emails after every meeting, queued in Outlook for the AE to send
- · Files notes back into the CRM so the manager's pipeline review has fresh data
First useful output
A Monday morning pipeline brief in the revops Teams channel: deals at risk, stalled, and worth pushing today.
Time to first output
Same day
How the work moves
| Trigger | Action | Outcome |
|---|---|---|
| Opportunity stage advances in Dynamics 365 or Salesforce | VYRA reads the recent activity, drafts a deal brief, pings the AE | AE opens Teams to a brief explaining what changed, what to do next, and which collateral to send |
| Last contact older than the deal stage's expected cadence | VYRA drafts a touch-base email in the AE's voice, queued in Outlook | Deal stays warm; AE confirms or edits the draft and clicks send |
| Monday 7am Eastern | VYRA posts a pipeline summary in the revops channel: at-risk, stalled, worth pushing | Manager arrives at a triage list, not a 200-record CRM report |
| Customer meeting ends with a Teams transcript | VYRA drafts the follow-up email and files notes back into the CRM | AE confirms the draft and approves the CRM update; pipeline review Friday has fresh data |
Connections this work requires
Wire Teams channels and chats
How the agent listens for @-mentions, posts threaded replies, and uses adaptive cards. Base wiring every other use case depends on.
Wire Dynamics 365
How the agent reads Dynamics 365 records and posts deal briefs, support escalations, and pipeline updates back into Teams.
Wire Outlook mail
How the agent reads shared Outlook mailboxes, drafts replies, and escalates urgent threads into Teams. Five-minute walkthrough for the workspace admin.
Recommended fidelic agent
AI Sales Engagement Coordinator
What the work costs
VYRA costs a small fraction of what a mid-market sales operations analyst costs. The agent does the parts of revops that scale: reading every deal every day, drafting briefs, pinging owners. A senior RevOps lead runs $8 to 12K/month fully loaded; the AE-to-AE conversations and the strategic pipeline calls stay with them. See the math on /pricing.
The boundary around this connection
VYRA currently does not:
- Send emails to customers without AE approval. Drafts queue in Outlook; the AE clicks send.
- Make pricing or discount commitments. The agent surfaces the deal context; the AE and manager negotiate.
- Replace the Friday pipeline review. The agent makes the review faster; it does not eliminate the human conversation about strategy.
Choose what to inspect next
- → Back to Microsoft Teams Review the complete connection and its related work.
- → See the Agents directory Compare the roles available to hire.
- → All integrations
Follow the connected questions
Start and work together includes this decision and the questions that usually change it.
Which systems should an AI agent connect to?
Connect the smallest set of systems needed to read the source, write the work product, and preserve the record the business already uses.
Inspect supported integrations →What data should an AI agent be allowed to access?
Grant only the systems and records required for the role. Keep credentials, customer boundaries, logs, and approval rules explicit.
Where should an AI agent’s work appear?
Use the environment where the right people can see the result, inspect the source trail, correct it, and make the next decision.