AI receptionist for small business: calls, bookings and handoffs
What an AI receptionist does on a real call, the rules that apply, a sample greeting and a pass/fail checklist to launch one safely.
Health scores built from Intercom conversations and tags, visible on the contact when that customer writes in.
Your support team talks to customers every day, yet they rarely know whether the person writing in is a happy account or one about to leave. This edition scores health from Intercom conversations, tone, contact frequency and open issues, joined with one more source such as billing. The score sits on the Intercom contact, so agents see it before they reply.

AI Customer Health Score for Intercom reads conversations, contacts and tags from Intercom, scores sentiment, contact frequency and unresolved issues together with one more system such as billing, and writes the result back to mapped contact attributes or tags. Support agents see account health inside the conversation. Agents see account health inside each conversation.
Support conversations are often the earliest sign that an account is unhappy, but that insight rarely leaves the inbox. Agents treat a frustrated key account the same as anyone else because they cannot see the bigger picture. This edition turns conversation patterns into a health score and puts it where agents work, so they can prioritize and escalate. The written scope sets out the mapping, the second source and the alerts before you order.
The health score is written back to mapped Intercom contact attributes or tags. Agents see account health inside the conversation and can adjust their tone and priority.
The score weighs sentiment, how often a customer gets in touch and unresolved issues from Intercom conversations. Repeat frustration builds into a visible signal rather than staying buried.
One more system, such as billing, is added to the Intercom data. A customer with a failed payment and a complaint can be spotted as a combined risk.
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $4,250 |
| Express | 15–25 working days | $5,000 |
| Rush | 10–20 working days | $5,750 |
Before you start: Export recent Intercom ratings and repeat-contact counts. Note any current tags your team uses to mark unhappy customers.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
The build price is a one-time payment. Expect roughly $20 to $150 a month in your own accounts for AI model usage, which grows with conversation volume, plus hosting or scheduling. Your Intercom plan and seats are unchanged, and any Intercom upgrade sits outside this build.
Usage during the build and testing is billed to you too.
Ask about running costsCustom Intercom objects, data outside the agreed mapping, a third system or a score per company workspace need a Change Quote. Add a note at checkout for a written quote. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionMonthly maintenance covers monitoring, fixes, updates, a health report and change hours, such as new conversation tags to weigh or a revised alert threshold. The hours scale with your build.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance works| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A CS platform charges another seat license beside Intercom | An Intercom specialist quotes per project | Ours is one fixed price, shown before you buy |
| Conversation signals | Most CS tools count tickets but ignore tone | Depends on the brief | Ours weighs tone, frequency and open issues together |
| Seen by support | Health lives in a tool agents never open | An agency build depends on what was agreed | Ours writes health onto the Intercom contact |
| Delivery | Syncing a new platform takes weeks | An agency usually takes several weeks, set per project | Ours has a fixed delivery time shown before you buy, with faster options |
It reads conversations, contacts, tags and help center articles through a two-way connection, and writes the score to the contact attributes or tags named in your documented field mapping. Data outside that mapping is not touched, and your Intercom workspace settings stay as they are.
Yes. Because the score is written to the contact as an attribute or tag, it appears alongside the conversation in the Intercom inbox. An agent can see at a glance that a customer is at risk and handle the reply, or escalate it, with that in mind.
Recent messages from each customer are assessed for tone, alongside how often they write in, how long their issues stay open and whether the same topic keeps returning. You decide how much each signal weighs, and the three-month back-test shows whether tone actually predicted cancellations for you.
Each delivery speed has one fixed price. The price panel shows standard, express and rush side by side before you pay, and the cart confirms your delivery date. Running costs of roughly $20 to $150 a month are separate and paid to your own providers.
Usually billing, such as Stripe, because Intercom shows how customers feel but not whether they are paying, downgrading or failing payments. Product usage data is the other common choice. One extra system is included; a third would need a Change Quote or an integration add-on.
An Intercom app access token and 30 minutes of an admin's time to agree the field mapping. The token is used only for the conversations, contacts and tags in that mapping, and it is never sent by email. Your Intercom plan and seats remain your own.
Order AI Customer Health Score for Intercom and conversation tone, frequency and open issues become a health score on every Intercom contact, visible before your agents reply.

Predicts churn risk and recommends the retention play for each at-risk account.

Flags accounts showing churn signals and recommends save actions.

Resolves customer questions across chat and email using your knowledge base and hands off complex cases.