GuruSup vs Intercom: AI Agents That Go Further

Intercom is built around messaging: a highly polished in-app chat, proactive messages and Fin, which answers in the chat with whatever is in your help center. GuruSup starts from your systems: its AI agents work across WhatsApp, email, web chat and voice, look things up in your tools and complete the request the customer is making.

To decide, think about what costs you the most today. If what matters is chat inside your product, with in-app messages and product tours, Intercom is a very good choice. If what swamps your team is repetitive queries that mean opening the ERP or the CRM before anyone can reply, you need agents with access to those systems and your business rules.

Yes. It currently runs accounts with several hundred new tickets every week and thousands of messages a month, with more than 2 million messages handled in total. On voice, an agent spins up for every incoming call, so the number of simultaneous calls is not a ceiling.

For complex processes, each use case gets its own specialist agent, for example bookings, pre-sales, after-sales or claims. A triage agent routes the conversations and integrations connect to each department's systems.

Not necessarily. There are two ways to work, and each one serves a different goal.

With Intercom still running: your team stays in Intercom while GuruSup handles the use cases you choose in a pilot. GuruSup connects to Intercom through its API to look up and update the data the process needs, such as contacts, conversations and history, and the exact scope is agreed with the team during implementation.

With GuruSup as your main platform: GuruSup takes over the channels and the inbox, with its own agents, metrics and escalation to people. It makes sense when you would rather run one operation than two tools side by side.

The agents work on top of the systems you already use by calling them through their APIs, without copying data into another database or forcing you to migrate. There are more than 350 integrations available, including support and CRM tools like Zendesk, Zoho Desk and HubSpot.

Usually all it takes is a system with an API and credentials with permissions for the actions you plan to automate. If an internal tool does not expose an API, other ways to connect it are explored during implementation. Custom integrations and complex processes are prepared together with the GuruSup team.

A triage agent does: it reads each incoming conversation and sends it to the agent that specialises in that use case. Once it is done, it can also create the ticket in whatever tool you use.

A person steps in in three cases: when the agent cannot resolve it, when the customer asks for one or when the use case is flagged as sensitive. The conversation shows up in the inbox as pending review, with the full history and, on the channels that allow it, a draft that can be edited before sending. If it is a call, it goes to the phone of the person on your team.

Yes. GuruSup covers WhatsApp, email, web chat and phone with text and voice agents. It detects each customer's language and replies in it, with 78 languages available and language switching within the same conversation.

Whatever the agent looks up in your systems during a conversation stays in its context for a while, around 24 hours, and is reused in the following steps so the customer is never asked again for details they already gave. Coverage per channel depends on the channels and systems you connect.

In stages: first channels and systems are connected, then a controlled pilot runs on a real high-volume use case, followed by launch and ongoing measurement. You start with three or four priority agents, not the whole operation.

While the pilot runs, your team keeps working in Intercom as usual. GuruSup's replies can start as drafts your team reviews and move to automatic once the results justify it. The knowledge and procedures you already have are the starting point for configuring the agents.

Seat licenses plus a fee for every Fin resolution versus volume-based pricing: you cannot compare them by looking at list prices. You need your real conversation volume and its channels, the size of your support team, how many conversations the AI would close, the integrations you need and what the rollout costs.

With GuruSup you pay on conversation volume, not per agent, so adding people to the team does not raise the price. The reliable way to compare is with your own data: in the demo we go through volumes, channels and systems and put together the scenario for your operation.

It depends on how much support you handle. GuruSup makes sense once you have more than 5 people in customer support and more than 5,000 messages a month: at that volume, automating complete requests pays off and paying on volume works out better than paying per seat and per resolution.

Below those numbers, a simpler chat tool or help desk is usually enough. The sensible move is to wait for volume to grow before setting up AI agents connected to your systems.