Rippit vs. Sierra for Conversation Analysis and Agents (2026): Differences, Pricing, and When to Use Both
Short answer: Sierra builds AI agents that handle customer conversations across chat, voice, email, SMS and WhatsApp.[1]
Rippit is built for one job: analyzing and acting on every customer conversation at scale.[2] It reads those conversations, plus your human-agent tickets, turns what it finds into structured data,[3] and shows whether issues were actually resolved and what to change. Rippit also runs AI agents of its own that monitor, analyze and act on that data;[2] they work in the background, not real-time with your customers.
Teams keep Sierra to run the AI agent and add Rippit as an independent layer that reads 100% of conversations.[4] Rippit publishes its pricing.[5] Sierra uses outcome-based pricing.[6]
Where Rippit and Sierra overlap is Sierra's conversation analytics capabilities.
Rippit vs. Sierra at a glance
| CRITERIA | Sierra | Rippit |
|---|---|---|
| What is it? | AI agent platform for customer experience across chat, voice, email, SMS and WhatsApp[1] | AI conversation analytics and agents for every team.[2] Rippit's agents analyze conversations; they don't talk to customers |
| Starting point | Your journeys, knowledge and brand guidelines, configured in no-code Agent Studio or described to Ghostwriter[7] | The conversations you already have: tickets, calls and chats (those contained by the bot as well as those handed over to human agents),[8] plus the survey data tied to them |
| Best fit | Teams automating customer conversations with AI agents | Large-scale analysis and agents across every conversation your company has, AI and human. One independent view, so product, CX and leadership can see what's resolved, what's not and why |
| Conversation analysis | Insights (CSAT, case resolution, custom dashboards)[9] and Explorer (natural-language deep research across thousands of conversations),[10] built into the Sierra platform | The core product. AI analyzes every conversation, with nothing sampled[2] |
| AI agent monitoring | Insights monitors and audits agent actions and alerts on issues like abuse attempts or performance drops[9] | An independent read on bot performance. Reads 100% of bot conversations to surface silent failures, unresolved issues and the intents the bot struggles with[11] |
| Human + AI conversations in one view | Insights tracks your Sierra agent's performance;[9] confirm coverage for conversations handled outside Sierra | Bot and human-agent conversations from your helpdesk sit in one dataset, so you can see where people succeed where the bot doesn't[11] |
| How teams use the data | Improve agent journeys and knowledge. Explorer recommends improvements,[10] and Expert Answers turns knowledge gaps into draft articles[12] | Describe the insight you want, and Rippit adds it as a field across every conversation (root cause, churn risk, resolution).[13] Reuse it in dashboards and follow-up questions, and deploy Rippit agents to act on findings |
| Customization | Custom dashboards and metrics in Insights,[9] plus natural-language questions in Explorer[10] | AI tags every conversation across 10+ dimensions, such as intent, root cause, churn signal and resolution[13] |
| What gets scanned, analyzed and acted on | Insights analyzes every conversation with your Sierra agent[9] | 100% of conversations in scope, with nothing sampled[5][2] |
| How it handles large datasets | Explorer finds answers across thousands of real conversations and runs continuously in the background[10] | Stores every conversation as structured, queryable data[3] that Rippit's agents and your team can enrich and aggregate across the full dataset |
| Traceability | Click any data point in a report to launch Explorer,[9] and its findings link to the conversations behind them[10] | Every result is a field on a specific conversation,[3] and each analysis step is documented, so any answer can be audited |
| Repeatability | Explorer runs continuously and sends weekly proactive briefings[10] | Turn any analysis or action into a repeatable Agent App that runs itself[2] |
| Setup | No-code Agent Studio; Ghostwriter builds agents from SOPs, transcripts and plain English[1][7] | Self-serve. Connect Zendesk, Intercom, Gong and Granola in one click[8] and go live in minutes[2] |
| Works with Sierra | Integrations connect Sierra to your systems[14] | Native Sierra integration. Analyzes Sierra conversations including escalations to human agents |
| Works with Claude | Deploys agents to channels including ChatGPT;[1] no connector found for querying Sierra data from Claude | MCP Server so Claude, Codex, Cursor, and more can query your conversation data directly |
| Public pricing | Outcome-based pricing, such as per resolved conversation; no public price list[6] | Free (includes $100 in AI credits); Starter $185/mo; Growth $495/mo; custom Enterprise[5] |
| Best starting question | "How do we resolve more customer conversations with AI agents?" | "Did our AI agent actually resolve the issue, and where did it fail?" |
What's the difference between Rippit and Sierra?
Sierra resolves customer conversations. Rippit analyzes them.
Sierra is an AI agent platform for customer experience.[1] Teams build agents in no-code Agent Studio or describe what they want to Ghostwriter, which builds agents from SOPs, transcripts and plain English, then deploy them across chat, voice, email, SMS and WhatsApp.[1][7]
Rippit is AI conversation analytics and agents, built for scale.[2] It connects to all of your conversation sources, analyzes every conversation, whether a bot or a person handled it,[2] and turns what it finds (intent, root cause, sentiment, churn signal, resolution) into fields you can filter, trend and action on.[13] Rippit's agents then monitor those fields, analyze them and act on what they find.[2] They work behind the scenes on your conversation data; Sierra's agents are the ones talking to customers.
Take a customer who asks an AI agent about a refund, gets a policy answer and closes the chat. On a dashboard, that conversation counts as handled. Two days later the customer writes in again, and a human agent issues the refund. Rippit reads both conversations in full, tags the first as unresolved, and shows how often that intent ends up with a human agent. Rippit can also take this further: Rippit agents can draft SOPs based on the results, for your team to use in improving Sierra.
How does Rippit analyze every conversation?
Rippit runs an AI engine built to label conversations in bulk: AI enriches every conversation[2] and stores the results as structured, queryable data,[3] so analysis and Rippit's agents can work across all of it. Rippit says it can analyze 10,000 conversations in one minute for under $1.[2] Questions then run on those stored fields across the full dataset, instead of rereading transcripts each time. For open-ended questions no existing field answers, Rippit also runs ad hoc deep dives[3] on up to 10,000 conversations at a time, and what they find can feed new analysis and agents.
That changes three things:
Can you use Rippit and Sierra together?
Yes. Keep Sierra to run your AI agent, and add Rippit as an independent layer that reads every conversation, bot and human. Rippit's native Sierra integration brings your Sierra conversations into Rippit. Rippit also connects to Zendesk, Intercom, Gong and Granola in one click for the conversations your human team handles.[8]
In Rippit's review of 2,345 of its own sales conversations from 2025–2026, 27 prospects were running or evaluating Sierra. The recurring reason they talked to Rippit wasn't to replace it. They wanted an independent check on AI-agent conversations, in the same place they review human agents and escalations.[4]
Using both fixes two common gaps:
- Bot reporting lives inside the bot platform. Sierra's Insights measures your Sierra agent's performance.[9] Rippit gives CX leaders an independent read that doesn't depend on any one AI agent vendor, so the same definitions hold if you add channels, add vendors or change your stack.[2]
- Bot and human outcomes sit in different places. Rippit puts both in one dataset. At Klaviyo, Rippit runs across 100% of bot conversations to identify "where humans were succeeding where the bot wasn't."[11]
Sierra's agents keep talking to your customers, while Rippit does the mass-scale enrichment behind them: it analyzes every conversation in scope,[2] stores each judgment as a field on that conversation,[13] and runs ad hoc deep dives on up to 10,000 conversations at a time for questions no existing field answers yet.[3]
Is containment the same as resolution?
No. Containment means the conversation stayed with the AI agent. Resolution means the customer's problem was solved. A customer can leave mid-conversation or accept an answer that doesn't fix the issue, and the conversation can still look contained. That distinction matters under outcome-based pricing, where Sierra charges for resolved conversations and, in most cases, not for unresolved ones.[6]
Rippit measures resolution by reading the conversation itself. Resolution is one of the dimensions AI tags on every conversation in one pass, alongside intent, root cause, sentiment, urgency and churn signal.[13]
Klaviyo used this to change how its bot escalates. Rippit surfaces silent failures in its bot conversations and feeds those patterns back into training. When a conversation signals an intent the bot consistently struggles with, it now triggers an immediate human handoff, "prioritizing speed to resolution over bot containment." Klaviyo reports a lower escalation rate and a higher true containment rate.[11]
How is Rippit different from Sierra Insights and Explorer?
Sierra's analytics are built into the platform you use to run your agent. Insights tracks your agent against metrics like CSAT and case resolution, with custom dashboards, experimentation and alerts.[9] Explorer answers natural-language questions across thousands of real conversations, runs continuously in the background and sends weekly briefings with recommendations.[10]
Rippit sits across tools - from your helpdesk,[2] so Sierra conversations and human-agent tickets get the same classification: intent, root cause, sentiment, churn signal and resolution.[13] It is also built for complex analytics and background Agents to support a wider variety of use cases.
Use Insights and Explorer to optimize your Sierra agent. Add Rippit for one independent view of every support conversation, and for questions beyond the bot: churn risk, product gaps and coaching.[15]
How much do Rippit and Sierra cost?
Rippit publishes its pricing. Paid plans bill AI credits at cost.[5]
Sierra doesn't publish a price list. Its pricing post describes outcome-based pricing: you pay when the agent achieves a specific outcome, such as a resolved conversation, a saved cancellation or an upsell, and in most cases there's no charge when a case is escalated or left unresolved.[6]
What do teams use Rippit for?
- Klaviyo went from reviewing fewer than 2% of its 600,000+ annual support incidents to analyzing 2.5 million conversations that had never been looked at. It runs Rippit across 100% of its bot conversations to catch silent failures and route hard intents to humans faster, and it analyzed a full month of product-launch conversations in two hours.[11]
- Checkr built predictive CSAT in Rippit that covers 100% of conversations, including chatbot conversations. Because customers communicate differently with a chatbot than with a human agent, Checkr built separate models for each source and combined them into one signal.[19]
When should you choose Sierra, Rippit, or both?
You want AI agents to handle customer conversations across chat, voice and messaging, with analytics built into the same platform.
You want to know what's happening across every support conversation, and you want business users to ask new questions without writing keyword rules.
You run Sierra and want an independent read on whether the AI agent actually resolves issues, how it compares with your human team, and what to change next.
Frequently asked questions
Is Rippit a Sierra alternative?
No. Sierra runs AI agents that talk to your customers.[1] Rippit doesn't answer customers; it analyzes the conversations your AI agents and human team have.[2]
Does Rippit integrate with Sierra?
Yes. Rippit's native Sierra integration brings in your Sierra conversations, so Rippit can analyze them alongside your human-agent tickets, including escalations.
Doesn't Sierra already have analytics?
Yes. Insights tracks agent performance[9] and Explorer answers questions across conversations.[10] Rippit adds an independent view across every helpdesk conversation, bot and human.[2]
Can Rippit tell whether an AI agent actually resolved the issue?
Yes. Resolution is one of the dimensions AI tags on every conversation,[13] so you can separate conversations that stayed with the bot from ones that were actually solved.[11]
Is Rippit cheaper than Sierra?
They do different jobs, so most teams budget for both. Rippit has a free plan and paid plans from $185/month.[5] Sierra uses outcome-based pricing.[6]
Does Rippit work with Claude?
Yes. Rippit supports MCP,[16] so Claude can query your conversation data directly.[17]
Can I trace a number back to the conversations behind it?
Yes. In Rippit, every result is a field on a specific conversation,[3] so you can audit any answer by opening the conversations and fields behind it.
Is Rippit the same company as MaestroQA?
Yes. MaestroQA is now Rippit: same founders, with a rebuilt AI-first platform. The company moved from maestroqa.com to rippit.com, and existing customer data, rubrics and integrations carried over.[18] Some Rippit help center articles still appear under the MaestroQA name and domain.
Sources
Rippit was formerly MaestroQA. Some sources below are hosted on the MaestroQA help center (help.maestroqa.com).[18]
- Sierra, homepage: https://sierra.ai/
- Rippit, homepage: https://www.rippit.com/
- Rippit, How It Works: https://www.rippit.com/how-it-works
- Rippit first-party research: AI analysis of 2,345 Rippit sales conversations (2025–2026), run on Rippit's own conversation analytics platform. Sierra came up in 36 of 2,345 conversations; 27 prospects were current or prospective Sierra customers.
- Rippit, Pricing: https://www.rippit.com/pricing
- Sierra, "Outcome-based pricing for AI Agents" (Dec. 2024): https://sierra.ai/blog/outcome-based-pricing-for-ai-agents
- Sierra, Agent Studio: https://sierra.ai/product/manage-your-ai-agent
- Rippit, Integrations: https://www.rippit.com/integrations
- Sierra, Insights: https://sierra.ai/product/insights
- Sierra, Explorer: https://sierra.ai/product/explorer
- Rippit, Klaviyo customer story: https://www.rippit.com/customer-story/klaviyo
- Sierra, "Insights 2.0: AI that improves your AI" (Nov. 2025): https://sierra.ai/blog/insights
- Rippit, Conversation Taxonomy playbook: https://www.rippit.com/playbooks/conversation-taxonomy
- Sierra, "Agent OS 2.0: from answers to memory and action": https://sierra.ai/blog/agent-os-2-0
- Rippit, Brex customer story: https://www.rippit.com/customer-story/brex
- Rippit, The Complete Guide to Conversation Analytics: https://www.rippit.com/playbooks/the-complete-guide-to-conversation-analytics
- Claude Help Center, Get started with custom connectors using remote MCP: https://support.claude.com/en/articles/11175166-get-started-with-custom-connectors-using-remote-mcp
- Rippit, "MaestroQA is now Rippit": https://www.rippit.com/news/maestroqa-is-now-rippit
- Rippit, Checkr customer story: https://www.rippit.com/customer-story/checkr
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