A full WhatsApp service desk, with no dependency on Salesforce.
The Nitzap Core replaces the CRM objects and delivers a service platform of its own. Tickets, contacts, queues, SLA and history live inside Nitzap, with API, MCP and webhooks to integrate with whatever the company already uses.
Not every service operation fits inside a CRM.
Nitzap was born inside Salesforce and it stays there. But many companies that need a well run WhatsApp operation have no CRM, do not want to pay a license per agent, or already keep their customer records in another system.
- The service team is large and per-user licensing kills the project.
- Customer records already live in the ERP, and duplicating them in the CRM makes no sense.
- The company wants the service running on its own infrastructure, by internal policy.
- The product needs a service API underneath, not a ready-made screen.
A ticket with complete history.
Every conversation becomes a record with assignment, events and messages, from first contact to closure. What was a standard object in Salesforce is a Nitzap object here.
- Queues and routing to send the conversation to the right team.
- Categories and SLA policies with a deadline per ticket type.
- Quick replies standardised by brand and by team.
- WhatsApp groups served inside the same flow.
MCP, webhooks and Flow to orchestrate.
Headless was made to talk to the rest of the operation. The MCP server gives context to AI agents, webhooks notify any system, and Flow builds the automation with no code.
- MCP servers with access keys and permissions per integration.
- Webhooks to integrate with any system, on any event.
- Flow to design bot, condition, lookup and reply on screen.
- Its own API per instance, isolated from other clients' data.
The whole platform, not just the channel.
The Core covers what a service operation needs to run on its own, from records to governance.
Service
Tickets with complete history, assignments, events and messages. Queues, routing, ticket categories, SLA policies, quick replies and WhatsApp groups.
Records
Accounts, contacts, organisations, users, roles, brands, shifts, tags, languages and per-user preferences.
Channels and campaigns
WhatsApp connections with the official API, WABA and Coexistence, approved templates and campaigns within Meta's rules.
Artificial intelligence
AI agents, conversation analysis and adjustments per agent and per conversation, with consumption control and a cost ceiling.
Governance and security
DLP for sensitive data, a Radar monitoring defined words, and a log of rule occurrences for audit.
Integrations
MCP servers, access keys and permissions, plus webhooks to integrate with any system.
Every client on their own instance.
This is not a shared environment with logical separation. Each client gets their own API and sees only their own data.
Isolation per instance
Own API and own data, with no neighbours. Each client sees only what is theirs.
Deploy where you need
Cloud managed by Datago or on-premise, on the company's own infrastructure, when internal policy requires keeping the data in house.
Panel, cost and logs
A server panel with cost per conversation followed closely, plus logs and events for audit and incident investigation.
Inside Salesforce or outside it.
It is the same service product. What changes is where the data lives and what the company needs to have in place first.
| Feature | Nitzap in Salesforce | Nitzap Headless |
|---|---|---|
| Where tickets, contacts and history live | Salesforce objects | Nitzap Core |
| CRM license per agent | Required | Not required |
| WhatsApp service with queues and SLA | ✓ | ✓ |
| Official Meta API, WABA and Coexistence | ✓ | ✓ |
| Campaigns with approved templates | ✓ | ✓ |
| AI agents and conversation analysis | ✓ | ✓ |
| MCP server and webhooks | ✓ | ✓ |
| Installation | Managed package in the org | Own instance, cloud or on-premise |
| Customer data inside the CRM | ✓ | Via integration |
Drag the table sideways to see all columns.
Anyone who already has Salesforce and wants service inside the CRM stays on standard Nitzap. Headless serves those with no CRM, those who do not want a license per agent, or those who need the platform on their own infrastructure.
From the instance to the first conversation.
No package to install in any org. What exists is a provisioned instance, connected to your channels and integrated with what you already run.
Instance provisioned
We bring the environment up in the cloud or on your server, with its own API and isolated access.
Channels and team connected
WhatsApp connections, queues, roles, shifts and SLA policies configured with your team.
Integration where it makes sense
MCP for the AI agents, webhooks for your system and Flow for the bot automation.
What people usually ask.
Do I need Salesforce to use Headless?
No. That is precisely the point. The Nitzap Core replaces the CRM objects and delivers tickets, contacts, queues, SLA and history on the platform itself. If the company later adopts Salesforce, the integration exists and the history is not lost.
What is the difference from the existing Nitzap?
It is the same service product. In standard Nitzap the data lives in Salesforce objects and each agent needs a CRM license. In Headless the data lives in the Nitzap Core, on its own instance, and there is no CRM license involved.
Can it run on our server?
Yes. Deployment is either in a cloud managed by Datago or on-premise, on the company's own infrastructure, when internal policy requires keeping data in house.
How does isolation between clients work?
Each client has their own instance, with its own API, and sees only their own data. It is not logical separation inside a shared environment.
What does the MCP server deliver in practice?
Context during the conversation. On the same screen, the agent sees what the assistants brought from the ERP, calendar, files and CRM, with keys and permissions controlled per integration.
How do you control AI cost?
There is AI tuning per agent and per conversation, with consumption control and a cost ceiling. Cost per conversation also shows in the infrastructure panel.
What do DLP and Radar do?
DLP identifies sensitive data moving through the conversation. Radar monitors words defined by the company. Both log a rule occurrence, and the log is available for audit.
Do you use the official Meta API?
Yes, WABA and Coexistence, with approved templates and campaigns within Meta rules. Datago is a Meta Tech Provider.
Let us design your instance.
Tell us how your service works today and where customer data flows. From there we size the instance, the channels and the integrations.
Rather talk now?
Sales team on WhatsApp, Monday to Friday, 9am to 6pm (BRT).
WhatsApp +55 27 99997-0276