MaestroQAvs
SupportmanThe MaestroQA alternative for Intercom teams.
MaestroQA rebranded to Rippit in March 2026 and is shifting from QA toward conversation analytics.
MaestroQA rebranded to Rippit in March 2026 and is steering away from “QA” toward AI conversation analytics. Its self-serve Agent Apps let a team run custom AI agents over conversation data, including a rough repeat-contact check, but nothing in the product keeps a persistent, evidence-backed record of one customer’s problem.
Supportman keeps it simple for Intercom teams: real-time CSAT and DSAT alerts in Slack, weekly reports, and AI quality scoring on every closed conversation, self-serve with published per-user pricing. It is also building Problem Episodes: a record that links a customer’s conversations about the same issue and flags it, with a quote as evidence, if the problem comes back or a promise gets forgotten.
Free trial · No credit card · Connects to Intercom & Slack in under 2 minutes · Visit MaestroQA ↗
Rating alerts and AI scoring, without building a QA program.
With MaestroQA
- Rebranded to Rippit in 2026 and pivoting from QA toward conversation analytics
- Paid plans jump from a free tier to $185/mo (Starter) and $495/mo (Growth), metered by agent runs
- Priced and built around running AI agents over conversation data, not real-time rating alerts
- Built for mid-market and enterprise QA programs
- More platform than many Intercom teams need for CSAT and scoring
With Supportman
- Built for Intercom, connect and go
- Per-user pricing from $5/user/mo, listed publicly
- Real-time CSAT & DSAT alerts in Slack
- AI quality scoring on every closed conversation
- Self-serve, no demo or engineering required
MaestroQA vs Supportman pricing, side by side.
Rippit (formerly MaestroQA) now publishes pricing per workspace, metered by agent runs: a free self-serve plan (100 agent runs/mo, $100 in AI credits), Starter at $185/mo, Growth at $495/mo, and a custom Enterprise tier. Supportman lists per-user pricing on the site and connects in minutes with no sales call.
MaestroQA
Free; $185–$495 / mo; Enterprise custom
- Model
- Per workspace, metered by agent runs
- Getting started
- Free self-serve plan
Supportman
$5–$15 / user / mo
- Model
- Per-user tiers, published (min $25/mo)
- Getting started
- Free trial, no credit card
| Team size | MaestroQA | Supportman |
|---|---|---|
| 5 agents | Free–$495/mo per workspace (by agent runs, not per agent) | $25/mo (Basic) or $75/mo (Pro with AI scoring) |
| 15 agents | Free–$495/mo per workspace (by agent runs, not per agent) | $75/mo (Basic) or $225/mo (Pro with AI scoring) |
| 30 agents | $495/mo Growth or custom Enterprise (by agent runs, not per agent) | $150/mo (Basic) or $450/mo (Pro with AI scoring) |
Supportman prices are per month, billed annually.
Switch from MaestroQA in a week.
- Export your MaestroQA scorecard as a reference when building Supportman’s rubric.
- Install Supportman on Intercom + Slack while MaestroQA is still running.
- Post DSAT ratings to Slack so agents keep alert coverage during the switch.
- Calibrate Supportman IQS against MaestroQA AutoQA on a shared sample of 25 threads.
- Retire MaestroQA reviewer assignments once weekly IQS trends replace your QA dashboard.
MaestroQA vs Supportman, feature by feature.
Every Supportman dashboard and Slack feature, next to what MaestroQA (now Rippit) documents publicly. Beta and in-build features are labelled as such; where we couldn't find public documentation, we say so rather than guess.
- Yes
- Partial
- Beta
- In build
- Add-on
- No
- Not documented
| Feature | MaestroQA | Supportman |
|---|---|---|
| Key differences | ||
| Pricing model | Per workspace, by agent-run volume | Per-user tiers, published |
| Starting price | Free plan; paid from $185 / mo | $5 / user / mo (min $25) |
| Built for | Mid-market & enterprise QA programs | Intercom-native |
| CSAT / DSAT to Slack | QA review workflows instead | Real-time alerts, per channel |
| AI conversation scoring | Automated QA scoring | IQS on every closed conversation |
| Manual review & calibration | Deep: scorecards, calibration, coaching | Not the focus |
| Tracks one customer’s problem across conversations | Custom Agent Apps can approximate repeat-contact checks; no built-in persistent record | Building Problem Episodes: links conversations, quoted evidence (in build) |
| Time to first value | Self-serve signup; Enterprise via demo | <2 minutes, self-serve |
| Real-time Slack loop | ||
| CSAT ratings posted to Slack in real time | Not documented | YesEvery rating, the moment it lands |
| Dedicated channel for bad ratings | Not documented | YesPro |
| Filter alerts by star rating or remark | Not documented | YesBy star rating, or only when a remark is left |
| Send a conversation to Slack from the inbox | No | YesIntercom inbox app, to a channel or DM |
| Conversation reminders | No | YesSet from the Intercom inbox |
| AI quality scoring | ||
| AI quality score on every closed conversation | YesAI grading and LLM classifiers | YesIQS, 0–100 |
| Per-criterion rubric breakdown | YesConfigurable rubrics | YesRubric chart on every scored conversation |
| Predicted CSAT for unrated conversations | YesPredictive CSAT on every conversation | YesCovers the ~90% customers never rate |
| Scores AI-agent and human conversations alike | Not documented | YesFin and humans, same rubric |
| Manual review scorecards & calibration | YesRubrics, grader QA, calibrations | NoNot the focus |
| Coaching workflows | Yes | PartialPer-agent reports & quality ranking |
| Dashboard & insights | ||
| Team quality dashboard | Yes | YesRated, positive, IQS, needs review |
| Bad-rating review queue | PartialVia assignment automations | Yes1★ and 2★ conversations |
| Quality trends & predicted-vs-actual CSAT | YesPredictive CSAT vs survey coverage | YesIQS trend, bad rate, model bias |
| Topic spikes & drift | YesConversation taxonomy and analytics | BetaSpiking / drifting / cooling, from Intercom Topics |
| Account health drift | PartialChurn-risk classifier | Beta28-day drift per account |
| Daily work queue (unanswered, unhappy, handed off) | No | BetaToday view |
| Conversation explorer with rating & score filters | Yes | YesDate, rating, remark, AI score |
| Per-agent quality ranking | Yes | YesRates that survive a thin week |
| Cross-customer voice-of-customer analytics | YesCore focus since the Rippit rebrand | PartialTopic trends only |
| Fin & AI agents | ||
| Fin vs human quality comparison | Not documented | YesBad-rating rate, Fin vs human-only |
| Fin conversation audit | PartialCustom Agent Apps over Intercom data | Beta |
| Independent of the AI agent it measures | Yes | Yes |
| Answers customers (AI agent) | NoAnalyzes conversations, doesn’t answer | NoMeasures, doesn’t answer |
| Reporting & workflow | ||
| Weekly team report in Slack | Not documented | YesFriday, before standup |
| Per-agent weekly reports by DM | PartialQA notifications via Slack | YesIncludes predicted CSAT & IQS |
| Approvals for refunds & exceptions in Slack | No | BetaRequested in Intercom, decided in Slack |
| Manager notes on conversations | PartialGrader comments | Beta |
| Closed doesn’t mean resolved | ||
| Tracks one customer’s problem across conversations | PartialAgent Apps can approximate repeats | In buildProblem Episodes |
| Alerts when a promise to a customer is missed | Not documented | In build |
| Platform, pricing & setup | ||
| Intercom integration | YesNative, on every plan | YesNative, connects in 2 minutes |
| Zendesk, Freshdesk & others | YesZendesk, Salesforce, Kustomer & more | NoIntercom only today |
| Voice / call coverage | YesTelephony integrations, e.g. Talkdesk | No |
| Published pricing | YesFree plan; paid from $185 / mo | Yes$5–$15 / user / mo |
| Self-serve free trial | YesFree plan with $100 AI credits | YesNo credit card |
| Time to first value | PartialSelf-serve signup; Enterprise sales-led | YesUnder 2 minutes |
MaestroQA details come from its public website, docs and pricing pages, checked September 2026. MaestroQA website ↗
When MaestroQA is the better pick.
MaestroQA (now Rippit) is a mature, highly rated platform (one of the strongest review bases in the category) for teams running a structured QA program: manual and automated scorecards, calibration, coaching, and a growing conversation-analytics layer. If you want a dedicated QA function and custom AI agents over your conversation data, it is a strong pick. Supportman is for Intercom teams who want the core signals (ratings as they land and an AI score on every conversation) without the platform and the procurement.
MaestroQA vs Supportman, answered.
Did MaestroQA change its name?
Yes. MaestroQA rebranded to Rippit in March 2026 and signaled a shift away from traditional “QA” toward AI conversation analytics. The MaestroQA name is now legacy.
Does MaestroQA / Rippit work with Intercom?
Yes, MaestroQA (Rippit) integrates with Intercom alongside Zendesk, Salesforce, Front, and Kustomer. The difference is approach: it is an AI conversation-analytics platform priced per workspace by agent runs, whereas Supportman is Intercom-native and focused on real-time rating alerts and AI scoring, priced per user.
How much does MaestroQA cost compared to Supportman?
Rippit (formerly MaestroQA) publishes per-workspace pricing metered by agent runs: a free plan (100 agent runs/mo, $100 in AI credits), Starter at $185/mo, Growth at $495/mo, and custom Enterprise. Supportman is priced per user: $5 per user per month for notifications and reports, $15 per user with AI evaluations, with a free trial and no credit card.
What does Supportman do?
Supportman sends Intercom CSAT and DSAT ratings to Slack in real time, emails weekly team reports, and runs AI quality scoring (IQS) on every closed conversation.
Do I have to book a demo to start?
No. Supportman is self-serve: connect Intercom and Slack and you are live in under two minutes.
Will Supportman replace a full QA platform?
For a large, formal QA program with calibration and manual scorecards, a dedicated platform goes deeper. Supportman covers the signals most Intercom teams act on daily (real-time rating alerts and AI scoring) at a published per-user price.
Can Rippit tell me whether a customer’s problem actually got fixed?
A Rippit customer could build a custom Agent App to look for repeat contacts, but there is no built-in, persistent record that follows one customer’s issue across conversations. That is exactly what Supportman is building with Problem Episodes (in build now): conversations from the same customer about the same issue get linked into one record, with a quoted flag if the customer comes back, a promise goes unkept, or a “closed” conversation was never actually resolved.
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