Data Panda brings your Fireflies.ai meeting transcripts, summaries and action items together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your sales, customer-success and operations teams use every day.
Fireflies.ai was founded in 2016 by Krish Ramineni and Sam Udotong, who met at an MIT hackathon and built six versions of the product before landing on the meeting-notetaker model the platform runs today. The model is simple: a bot called Fred joins a Zoom, Microsoft Teams or Google Meet call as a participant, records and transcribes the conversation, and writes back a summary, action items and topic tags. The company is based in Miami, claims usage across half a million companies, and supports transcription in around a hundred languages with speaker recognition.
The slot Fireflies sits in is broader than a sales-only tool. Sales reps use it for call recap, customer-success uses it for handoff notes, product teams use it for user-research interviews, and operations leads use it to keep meeting decisions out of private notebooks. The point of pulling Fireflies into a warehouse is the same idea applied at scale: a transcript is interesting, but a transcript joined to the CRM deal, the support ticket, the product feedback log or the hiring pipeline is a record the rest of the business can act on. In a warehouse, action items stop being a Slack DM and start being a row that can be assigned, tracked and reported.
Topics, action items and meeting volume per team and per account, on data that refreshes with the rest of the warehouse.
Let a Fireflies summary fire the rest of the stack instead of sitting in an email.
Turn the transcript pile into scoring the team can defend.
Internal tools on Fireflies data for sales, CS and product leadership.
A list of concrete reports, automations and AI features we have built on Fireflies.ai data. Pick the one that matches your situation.
Are the action items in our recaps getting done?
Action items extracted by Fireflies joined to whatever ticket, task or CRM activity should have followed. Shows the share of recaps that produced a real downstream action versus the share where the action lived in a summary nobody opened, broken down per team and per owner.
Which customers raise which topics most often, and how does that map to renewal?
Topic clusters from CS and sales calls per account, joined to renewal date, ARR and product usage. The accounts repeating the same blocker on three calls in a row stand out next to the accounts repeating the same praise, and renewal conversations land with the actual call evidence.
Where are competitors getting mentioned, and in which segments?
Competitor names tagged on transcripts, counted per segment, deal stage and outcome. Shows the segments where a specific competitor is now standard procurement comparison and the segments where they have not arrived yet, on the recordings the team already produces.
Account meeting volume and topic mix joined to ARR and renewal date. Finance and RevOps see which accounts produce a lot of CS hours without renewal lift and which ones convert call time into expansion.
Action-item completion per rep and per deal, with topic and competitor mentions per account. Coaching moves from anecdote about the call to the specific recap that did or did not get followed up on.
Topic clustering across customer calls in one view, refreshing with the warehouse. Product, support and CS leads work from the same evidence base instead of three exports of the same week.
Fireflies meeting summaries, action items and topic tags push onto the matching Salesforce opportunity as fields and timeline events. Reps stop pasting recap blocks into the activity log and forecast reviews walk in with the conversation that moved each deal.
Fireflies transcripts and action items land on the HubSpot contact and the linked deal. Sales and CS work from one timeline per account, and the recap stops being a separate email that lives in someone's inbox.
Each Fireflies summary creates a Notion page in the right team workspace, with action items as a checklist and the transcript link in the source field. Product, CS and ops teams get a searchable archive of customer voice without anyone typing notes a second time.
Once a Fireflies meeting closes, the summary and action items post to the matching Slack channel, customer for CS, deal for sales, project for ops. The people who needed the outcome see it where they already work, instead of waiting for the recap email to bubble up.
These are the 1 tables we currently pull from Fireflies.ai into your warehouse. Query them directly in SQL, join them to the rest of your stack, or build reports on top.
Missing a table you need? We can extend the sync. Tell us what is missing and we will build it for you.
You keep the reporting tool you already have. We connect it to the warehouse where your Fireflies.ai data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Consent is a workflow choice, not a Fireflies setting. The bot announces itself when it joins and admins can require an explicit on-record disclosure, and most teams pair that with a calendar invite line and an internal policy on which meeting types may be recorded. Once a recording exists, our connector pulls the transcript, summary and action-item metadata into the warehouse on the same retention rules as the rest of your customer data, with redaction and PII rules agreed before the content lands.
Fireflies covers a broader set of meetings: CS calls, product-research interviews, hiring screens and internal syncs, on top of sales. Gong is built around the sales-revenue-intelligence workflow with deal coaching and scorecards. Teams that want call recap and a searchable transcript archive across the company sit closer to Fireflies. Teams that want a deep B2B-sales conversation-intelligence layer with deal-health scoring sit closer to Gong, and the two often coexist in the same company.
We review your Fireflies.ai setup and the systems around it. Together we pick the first thing worth building.