Data Panda brings your Telegram bot conversations, channel posts and broadcast metadata 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 support, marketing and operations teams use every day.
Telegram is a cloud-based messaging platform with about a billion monthly active users and a strong following across the EU, MENA, the CIS region and South-East Asia. The product surface that matters for B2B sits in three places: bots built on the Bot API, channels that broadcast to unlimited subscribers, and groups that hold conversations with up to two hundred thousand members. The Bot API has no per-message or per-conversation fee, which is the structural difference with WhatsApp Business.
One nuance to keep on the table from the start: end-to-end encryption only applies to Secret Chats between two phones. Regular one-to-one chats, groups, channels and everything that flows through the Bot API are stored on Telegram's servers and accessible to whatever account or bot is in the room. For business use that is mostly a feature, because it is what lets a bot keep state, hand a thread to a human agent and feed a warehouse, but it does change how you classify the channel for privacy and DPO sign-off compared with the consumer messaging story Telegram tells in the press.
Volume, response time and broadcast reach in one place, instead of a screenshot the bot operator pastes in chat.
Let Telegram bot updates trigger work in the systems where the answer needs to land.
Put Telegram conversation and broadcast data behind AI that helps route, classify and forecast, on metadata first and message bodies only where the use case justifies it.
Small internal tools on Telegram metadata for support, marketing and community teams.
A list of concrete reports, automations and AI features we have built on Telegram data. Pick the one that matches your situation.
What does our Telegram channel really reach versus what we pay for elsewhere?
Views, forwards and click-through per post, against the cost of reaching the same audience on a paid channel like WhatsApp utility templates or sponsored social. Marketing leadership sees where the free Bot API and channel reach earn their keep, instead of guessing whether the Telegram audience is worth the editorial effort.
How fast does our bot answer, and how often does it have to hand a thread to a human?
Median and tail response time per intent, with the share of threads that escalate to a human agent and the reason. Support leads see which intents the bot covers cleanly and which ones cost agent time, which is the input for the next training round on the bot.
Which posts are travelling beyond our own subscriber base?
Forward rate and view-to-subscriber ratio per post, with the topic and posting time attached. Content leads see which formats earn organic reach in groups and other channels, which is the closest thing Telegram offers to a paid-amplification dashboard.
Channel cost on Telegram is close to zero on the Bot API itself, so the question becomes opportunity cost: editorial time on channels and bot maintenance, weighed against the reach those produce. Finance gets the comparison with paid channels in one view.
Bot threads linked to accounts and opportunities. Sales sees which prospects engage through the bot, which ones convert after a channel post, and which regions Telegram is moving the needle in.
Support, community and marketing-ops in one view. The team sees bot response time, handover ratio, channel reach decay and group activity on data that refreshes with the rest of the warehouse, not on a screenshot from the bot console.
Inbound bot threads create or update the matching HubSpot contact, and HubSpot lifecycle changes push a notification back into the Telegram bot for the rep that owns the account. Sales sees the Telegram leg on the contact timeline, and the rep gets the new-lead ping on the same app the prospect is already chatting on.
When a bot intent crosses the handover threshold, the thread opens or updates a Zendesk ticket with language, region and the last few bot turns attached, and ticket status flows back so the customer sees one coherent reply. Support leads stop juggling a separate bot console and a helpdesk inbox for the same conversation.
Channel posts under their reach baseline, bot threads stuck waiting on a handover and subscriber drops fan out as Slack alerts to the right channel, with a deep link back to the Telegram thread or post. The team that owns the customer-facing Telegram presence works from Slack, where the rest of the company already lives, instead of asking everyone to install another app.
Klaviyo segments by country, language and lifecycle stage trigger the right Telegram channel post or bot broadcast through your bot account, with the cost compared against the WhatsApp or email send for the same audience. Ecommerce reaches the regions where Telegram already has the audience, on a channel that does not invoice per conversation.
You keep the reporting tool you already have. We connect it to the warehouse where your Telegram 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.
By default we pull the metadata your bot account already has access to: chat id, message id, sender, timestamps, message type, channel post stats and update events. Message body content is technically available through the Bot API, but we keep it out of the default scope and only enable it where the use case (intent classification, summarisation) justifies it and the privacy conversation has happened first. Channel posts published by your own account are public-by-default and pulled in full, because that is what you posted to a public audience.
Telegram only applies end-to-end encryption to Secret Chats, which exist between two phones and are not part of the Bot API. Regular chats, groups, channels and any conversation a bot is in are stored on Telegram's servers and accessible to the participating accounts and bots. For business use that scope is what makes the channel work: a bot can keep state, escalate to a human and feed a warehouse. It does mean you should classify Telegram alongside other server-stored channels for DPO sign-off, not in the same bucket as a true end-to-end-encrypted messenger.
We review your Telegram setup and the systems around it. Together we pick the first thing worth building.