AI chatbot for Jetpack CRM: contact-aware conversations on your site
SleekAI maps Jetpack CRM contacts, companies, transactions, and invoices into the bot's context, so a logged-in customer gets answers rooted in their actual record rather than a generic FAQ. Bring your own OpenAI, Anthropic, Google, or OpenRouter key.
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A chatbot that speaks your customers' CRM record
Jetpack CRM stores contacts as the zerobscrm-customers post type, companies as zerobscrm-company, transactions, invoices, and quotes in their own custom tables, and contact custom fields in postmeta. SleekAI's data-source wizard exposes those records as named variables, so when a logged-in customer asks 'what's my balance' the system message already carries the relevant invoices and last transaction.
The bot can answer specifically. It can quote the last invoice amount and due date, point to a pending quote, confirm whether a payment cleared, and explain what a status like 'Refunded' or 'On Hold' means inside this account. None of that requires a separate dashboard, because the data already lives in Jetpack CRM and the bot reads it on the same request.
Display conditions scope the bot by post type, taxonomy term, user role, logged-in state, and URL pattern. A common setup is a customer-portal bot scoped to logged-in users that has access to CRM data, plus a public marketing bot that has none. Every conversation is logged inside WordPress with model, token usage, and page URL, so the support team can audit answers before scaling the bot to a wider segment.
Workflow
How SleekAI plugs into Jetpack CRM
Map CRM data
Scope by role
Bring your own key
Audit and improve
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A typical Jetpack CRM portal conversation
Comparison
Generic chatbot vs SleekAI for Jetpack CRM
Generic chatbot
- Doesn't know your CRM contacts or companies
- Can't see invoices, transactions, or quotes
- Invents balances and payment status
- Doesn't respect per-customer data boundaries
- Has no awareness of contact custom fields
SleekAI chatbot
- Reads Jetpack CRM contacts, companies, and transactions
- Knows the logged-in customer's invoices and balance
- Quotes status from real records, not made-up history
- Display conditions for portal-only widgets
- Logs every conversation with model and page URL
Features
What SleekAI gives you for Jetpack CRM
Contact-aware replies
The system message includes the logged-in contact's name, status, company, recent transactions, and open invoices, so answers reference the right record on the first reply.
Strict per-user data
Only the active contact's fields land in the prompt. The bot never has access to a full export, so a logged-in customer can't read another customer's balance or invoice through the conversation.
Invoice and quote context
Map invoices, quotes, and transactions and the bot can answer due dates, statuses, and amounts directly. Manual lookups in the admin go away for the common questions.
Use cases
Where teams use SleekAI for Jetpack CRM
Customer-portal support
Logged-in customers ask about balances, invoice statuses, and last payments, and get accurate answers from their own CRM record rather than waiting on email.
Lead intake
A public bot asks scoping questions, then creates a Jetpack CRM contact with company, channel, and notes via the JS API, so leads land in the CRM with context, not just an email.
Upsell on context
When a long-time client asks about a service they don't yet have, the bot can mention the right upgrade with real pricing pulled from a service catalog you map separately.
The bigger picture
Why CRM-aware AI matters for service businesses
Service businesses lose more time to status questions than to actual work. Is my invoice paid. When does my retainer renew.
Did you receive the file I sent. Each of those is a five-second answer if the assistant can see the CRM record, and a five-minute interruption if it has to be routed through a human. Jetpack CRM already holds the contact, company, transactions, invoices, and quotes, but exposing that to a chatbot usually means a custom integration.
A generic chatbot will not know that the May invoice is paid, that the brand-refresh quote is valid until June 1, or that the client is on the Priority support tag and deserves a quicker tone. SleekAI surfaces those fields as variables on the system message, so the model can answer accurately for the logged-in contact and only the logged-in contact. The result is a portal that feels staffed when nobody is at the desk.
Support leads also get a quiet record of which questions repeat, which is the cheapest way to find the policy lines that need to be written into the contact welcome email rather than the chat over and over.
Questions
Common questions about SleekAI for Jetpack CRM
Yes. When a user is logged in and their WordPress user is linked to a Jetpack CRM contact, SleekAI can include the contact's name, status, company, custom fields, transactions, invoices, and quotes in the system message. Only that user's data ends up in the prompt, so the bot can't leak another customer's record.
Yes. Jetpack CRM stores invoices, quotes, and transactions in their own tables. SleekAI maps the relevant fields, including total, status, due date, and linked contact. The bot can quote an outstanding amount or confirm whether a recent payment cleared without the team running a manual lookup in the admin.
Yes. Display conditions support logged-in state, user role, and URL pattern, so a portal-only bot with CRM data can run on the account pages while a public marketing bot with no CRM access runs on the rest of the site. Both live under the same SleekAI install in multibot.
Out of the box the bot answers and qualifies. For creation flows, the JS API and PHP embed let you forward the structured outcome of the conversation to a custom endpoint that inserts a contact, applies tags, or attaches a note via Jetpack CRM's own API. Most teams use that for lead intake, not for editing existing contacts.
Yes. SleekAI exposes the custom fields and tags you map on the contact and the company. The system message can then reference whether the contact is a 'Retainer client' or has the 'Priority support' tag, and the model can use those flags to shape its replies without you hard-coding logic.
Inside WordPress, with user, model, token usage, and page URL on each conversation. The support lead can review the log to spot tone issues, recurring billing questions, or confusion around statuses, and feed those back into the system message or the CRM's own status descriptions.
Yes. Jetpack CRM links contacts to companies, and SleekAI can expose both records together. The bot can answer 'how much does our company owe in total' by reading the linked invoices on the company record, not just the individual contact, if you map the relationship that way.
Yes. Each chatbot under multibot uses its own provider and model. A fast model is fine for invoice lookups, while a stronger model can handle the qualification logic on a complex lead-intake bot. Both run on your own provider keys so usage stays on your account.
Pricing
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