Rippit vs. Microsoft Copilot for Conversation Analysis and Agents (2026): When to Use Copilot Alone, and When to Add Rippit
Short answer: Microsoft Copilot is an AI assistant built into Microsoft 365 for reasoning, writing and analysis over your work content.[1] Rippit is built for one job: analyzing every customer conversation at scale.[2] On its own, Copilot works with what it pulls into each response from uploads, Microsoft Graph or the web,[1] so large datasets get searched or summarized rather than read in full.
Rippit reads every conversation, turns what it finds into structured data,[3] and runs AI agents that monitor, analyze and act on that data.[2] Connect the two over MCP, and Copilot agents can draw on Rippit's full dataset for their own analysis and actions.[4]
Rippit vs. Microsoft Copilot at a glance
| CRITERIA | Microsoft Copilot (on its own) | Rippit |
|---|---|---|
| What is it? | AI assistant built into Microsoft 365 for reasoning, writing and analysis over your work content[1] | AI conversation analytics and agents for every team[2] |
| Best for | Reasoning over a set of conversations you can paste or upload, alongside your Microsoft 365 documents | Large-scale analysis and agents across every conversation your company has |
| How much it can read | Microsoft doesn't publish a context window; standard file upload limits apply[5] | Every conversation in scope, in full[6] |
| How it handles large datasets | Pulls relevant content from your Microsoft 365 data through Microsoft Graph and Work IQ.[1] Copilot Studio agents can index up to 500 knowledge sources[7] | Stores every conversation as structured, queryable data[3] that agents and people can enrich and aggregate across the full dataset |
| What gets scanned, analyzed and acted on | Whatever it pulls in for each prompt from uploads, Microsoft Graph or the web[1] | 100% of conversations in scope, with nothing sampled[6][2] |
| Judgment fields at scale | The Analyst agent calculates statistics and trends from spreadsheets and CSVs;[8] judgment calls like churn risk require reading each conversation | AI tags every conversation across 10+ dimensions, such as intent, root cause, churn signal and resolution[9] |
| Traceability | Answers draw on whatever content was retrieved for each prompt, which can be hard to reconstruct afterward[1] | Every result is a field on a specific conversation,[3] and each analysis step is documented, so any answer can be audited |
| Repeatability | Up to 10 scheduled prompts with a Copilot license;[10] Copilot Studio agents can run on a recurrence trigger[11] | Turn any analysis or action into a repeatable Agent App that runs itself[2] |
| Setup | Copilot Chat comes with eligible Microsoft 365 plans;[12] MCP servers connect to agents built in Copilot Studio[4] | Self-serve. Connect Zendesk, Intercom, Granola, Gong and more in one click[13] and go live in minutes |
| Works with Copilot | Connects to outside tools and data through connectors and MCP in Copilot Studio[4] | MCP Server so Copilot Studio agents, Claude, ChatGPT, Codex, Cursor, and more can query your conversation data directly |
| Public pricing | Copilot Chat included with eligible Microsoft 365 plans; Microsoft 365 Copilot Business from $18/user/mo billed annually;[12] Microsoft 365 Copilot $30/user/mo billed annually;[14] Copilot Studio $200 per 25,000-credit pack/mo[15] | Free (includes $100 in AI credits); Starter $185/mo; Growth $495/mo; custom Enterprise[6] |
| Best starting question | "Read these 20 escalations and tell me what went wrong." | "What's actually driving our CSAT across all conversations in the last 60 days, including for customers who never answer a survey?" |
What's the difference between Rippit and Microsoft Copilot?
Microsoft Copilot is an AI assistant for your work content.[1] It writes, analyzes uploaded files and data,[5] and connects to outside tools through connectors and MCP in Copilot Studio.[4] Give it a handful of escalations and it will find the pattern, draft the fix and write the exec summary.
Rippit is AI conversation analytics and agents, built for scale.[2] It connects to all of your conversation sources,[13] reads every conversation, and turns what it finds (intent, root cause, sentiment, churn signal, resolution) into structured, queryable fields.[9] Agents then monitor those fields, analyze them and act on what they find.[2] Rippit's own guide puts the split plainly: general assistants are great for ad hoc reading, but they weren't built to operationalize conversation data at scale.[16]
Copilot isn't a database; Rippit is a database built for your conversations. Copilot can find and summarize content across your Microsoft 365 data, but on its own it can't analyze raw conversations beyond what it pulls into each response,[1] plus the workarounds described below.
Why does large-scale conversation analysis need every conversation?
Because a sample can't tell you how often something happens. Conversation analytics and agents that read and act on 100% of conversations remove "the selection bias of a small, self-selected slice."[16]
Rare signals are where samples fail. If 2% of conversations contain a churn signal, a 50-conversation sample catches one of them, maybe.[17] The patterns that matter most, such as an emerging bug, a confusing policy or a competitor coming up in renewals, often start small.
Volume makes this unavoidable. Klaviyo handles more than 600,000 support incidents a year, and before Rippit it reviewed fewer than 2% of them.[18] No chat window holds a year of conversations like that, so an answer drawn from one has to rest on part of the data.
How many conversations can Microsoft Copilot analyze on its own?
As many as it pulls into a single response. Microsoft doesn't publish a context window for Copilot Chat or Microsoft 365 Copilot, and says standard file upload limits apply.[5] With a Microsoft 365 Copilot license, Copilot grounds each answer in organizational data from Microsoft Graph and Work IQ, pulling in relevant information automatically.[1] That's built for finding the right documents, not for reading every ticket from the past year.
Copilot has good tools for working past that limit, and each changes what the answer rests on:
- File uploads let Copilot Chat reason over Word, Excel and PDF files, subject to standard upload limits.[5]
- Microsoft Graph grounding pulls relevant content from your Microsoft 365 data automatically on Microsoft 365 Copilot licenses.[1]
- Copilot Studio agents can draw on up to 500 knowledge sources, though Microsoft notes these agents can't write and run code over structured files, so "responses to analytical questions might not be optimal."[7]
- The Analyst agent calculates statistics, trends and outliers from Excel, CSV and other data,[8] which handles existing columns, like ticket counts by tag.
The gap is judgment at scale. Answering "what share of tickets show churn risk?" means reading each conversation. With retrieval, sampling or summaries, a large-scale count can rest on part of the data, and it's hard to tell which part from the answer alone.
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 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 Microsoft Copilot together?
Yes, and that's the recommended setup. Rippit supports MCP,[16] and Copilot Studio agents can connect to existing MCP servers.[4] Microsoft 365 Copilot users can build internal agents in Copilot Studio at no additional cost.[15] Connect Rippit once, and a Copilot agent can query your full conversation dataset.
In Rippit's review of 2,345 of its own sales conversations from 2025-2026, 16% of prospects (375) said they already use a general-purpose AI assistant to analyze customer conversations, or were considering building that analysis themselves. The recurring reasons they looked at Rippit: manually exporting tickets to CSVs, narrowing time frames to fit uploads, hitting usage limits, and wanting analysis that covers every conversation.[19]
Here's how the work divides:
- Rippit does the mass-scale enrichment. It analyzes every conversation in scope[2] and stores each judgment as a field on that conversation.[9]
- Rippit runs the deep dives. Ad hoc analysis on up to 10,000 conversations at a time, for questions no existing field answers yet.[3]
- Copilot provides the strategy. It decides which Rippit MCP tools to use to answer your question.[16]
- The analysis repeats. A question you answer once can become a Copilot Studio agent that runs on a recurrence trigger, so next month's run uses the same definition on new conversations,[11] or you can turn it into an Agent App in Rippit that runs itself.[2]
How much do Rippit and Microsoft Copilot cost?
Both publish their pricing. Rippit bills AI credits at cost on paid plans.[6]
Rippit
- Free: 100 Agent Runs/month, $100 in AI credits included[6]
- Starter: $185/month, 300 Agent Runs[6]
- Growth: $495/month, 1,000 Agent Runs[6]
- Enterprise: custom pricing, including SSO, advanced integrations and a dedicated AI Agent Specialist[6]
Microsoft Copilot
- Copilot Chat: included at no additional cost with eligible Microsoft 365 plans[12]
- Microsoft 365 Copilot Business: from $18/user/month billed annually ($25.20 monthly), as an add-on to eligible Microsoft 365 Business plans[12]
- Microsoft 365 Business Standard or Premium with Copilot: $23.50 or $32/user/month billed annually[12]
- Microsoft 365 Copilot (enterprise): $30/user/month billed annually[14]
- Copilot Studio: $200/month per pack of 25,000 Copilot Credits, with pay-as-you-go and prepaid options[15]
The two aren't substitutes: teams using both keep their Copilot licenses and add a Rippit plan sized to their conversation volume.
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 analyzed a full month of conversations in two hours during a product launch.[18]
- Checkr found that surveys captured fewer than 10% of its interactions, so it built predictive CSAT in Rippit that covers 100% of conversations. A late-night CEO question about background checks in one state had a detailed answer by morning.[20]
- Brex replaced sampling with AI review of 100% of conversations and found churn risk in 3% of them, a signal a small sample would likely miss.[21]
When should you use Microsoft Copilot alone, Rippit, or both?
You're working with a handful of conversations you can paste or upload, and you want to read them, summarize them or draft from them.
You need answers, and agents that act on them, across every conversation your company has, in sales, support, success and chatbots, with counts you can trust because nothing was sampled.
You want to ask questions in Copilot and get answers drawn from every conversation, not a sample, with each number traceable to the conversations behind it. For any team already using Copilot to understand customers, this is the setup to choose.
Frequently asked questions
Is Rippit a Microsoft Copilot alternative?
No. Rippit is the conversation data layer, and Copilot is a general-purpose assistant. They work best together, with Copilot agents querying Rippit over MCP.[16]
Can Microsoft Copilot analyze all my support tickets?
Microsoft doesn't publish a context window for Copilot,[5] and Microsoft 365 Copilot pulls relevant content into each response rather than reading everything.[1] For counts across a full ticket history, connect Copilot to Rippit, which analyzes every conversation.[2]
Does Microsoft Copilot sample my conversations?
Copilot answers from the content it pulls into each response from uploads, Microsoft Graph or the web.[1] Rippit reads every conversation, so answers don't depend on which ones were loaded.[2]
Does Rippit analyze 100% of conversations?
Yes, every conversation in the scope you choose,[6] with nothing sampled.[2]
Does Rippit work with Microsoft Copilot?
Yes. Rippit supports MCP,[16] and agents built in Copilot Studio can connect to existing MCP servers.[4]
Can I trace a number back to the conversations behind it?
Yes, with 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 and integrations carried over.[22] 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).[22]
- Microsoft Learn, Microsoft 365 Copilot overview: https://learn.microsoft.com/en-us/copilot/microsoft-365/microsoft-365-copilot-overview
- Rippit, homepage: https://www.rippit.com/
- Rippit, How It Works: https://www.rippit.com/how-it-works
- Microsoft Learn, Connect your agent to an existing Model Context Protocol (MCP) server (Copilot Studio): https://learn.microsoft.com/en-us/microsoft-copilot-studio/mcp-add-existing-server-to-agent
- Microsoft Learn, Frequently asked questions about Microsoft Copilot Chat: https://learn.microsoft.com/en-us/copilot/faq
- Rippit, Pricing: https://www.rippit.com/pricing
- Microsoft Learn, Quotas and limits (Copilot Studio): https://learn.microsoft.com/en-us/microsoft-copilot-studio/requirements-quotas
- Microsoft Support, Get started with Analyst in Microsoft Copilot: https://support.microsoft.com/en-us/microsoft-365-copilot/get-started-with-analyst-in-microsoft-365-copilot
- Rippit, Conversation Taxonomy playbook: https://www.rippit.com/playbooks/conversation-taxonomy
- Microsoft Support, Schedule your most used Copilot prompts: https://support.microsoft.com/en-us/microsoft-365-copilot/schedule-your-most-used-copilot-prompts
- Microsoft Learn, Event triggers overview (Copilot Studio): https://learn.microsoft.com/en-us/microsoft-copilot-studio/authoring-triggers-about
- Microsoft, Microsoft Copilot plans and pricing for business: https://www.microsoft.com/en-us/microsoft-365-copilot/pricing
- Rippit, Integrations: https://www.rippit.com/integrations
- Microsoft, Microsoft Copilot plans and pricing for enterprise: https://www.microsoft.com/en-us/copilot/pricing/enterprise
- Microsoft, Copilot Studio pricing: https://www.microsoft.com/en-us/microsoft-365-copilot/pricing/copilot-studio
- Rippit, The Complete Guide to Conversation Analytics: https://www.rippit.com/playbooks/the-complete-guide-to-conversation-analytics
- Rippit, Load Testing Conversation Analysis in Snowflake (June 2026): https://www.rippit.com/research/load-testing-conversation-analysis-in-snowflake
- Rippit, Klaviyo customer story: https://www.rippit.com/customer-story/klaviyo
- Rippit first-party research: AI analysis of 2,345 Rippit sales conversations (2025-2026), run on Rippit's own conversation analytics platform. 375 of 2,345 prospects (16%) used or were evaluating a general-purpose AI assistant for DIY conversation analysis.
- Rippit, Checkr customer story: https://www.rippit.com/customer-story/checkr
- Rippit, Brex customer story: https://www.rippit.com/customer-story/brex
- Rippit, "MaestroQA is now Rippit": https://www.rippit.com/news/maestroqa-is-now-rippit
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