---
title: "Agnost AI vs Enterpret: which should you use to analyze AI agent conversations?"
description: "Use Enterpret to analyze AI agent chats as one feedback channel next to support tickets, calls, reviews, and surveys, weighted by account revenue. Use Agnost AI to instrument your own agent: it reads conversations with their tool calls, checks them against intents and plain-language rules, and opens pull requests for recurring failures. Many teams need only one."
author: "Agnost AI Team"
datePublished: "2026-10-29T00:00:00.000Z"
dateModified: "2026-10-29T00:00:00.000Z"
canonical: "https://agnost.ai/blog/agnost-vs-enterpret/"
tags: ["Tool Comparison","Comparisons","Conversation Analytics","Customer Feedback"]
---

# Agnost AI vs Enterpret: which should you use to analyze AI agent conversations?

Use Enterpret to analyze AI agent chats as one feedback channel next to support tickets, calls, reviews, and surveys, weighted by account revenue. Use Agnost AI to instrument your own agent: it reads conversations with their tool calls, checks them against intents and plain-language rules, and opens pull requests for recurring failures. Many teams need only one.

Enterpret and Agnost AI both read AI agent conversations, but for different jobs. Pick Enterpret if your question is "what are customers telling us across every channel, and which accounts does it affect", and your agent's chats are one input among tickets, calls, reviews, and surveys. Pick Agnost AI if you build the agent and your question is "where does it fail users, why, and what should we change", with the tool calls and traces behind every conversation.

We make Agnost AI. Every Enterpret claim below comes from Enterpret's own website, checked on 2026-10-29. For the wider field, see [the best conversation analytics tools for AI agents](/blog/best-conversation-analytics-tools-ai-agents/).

## Feature comparison


| | Agnost AI | Enterpret |
|---|---|---|
| **Built for** | Teams that build and ship their own AI agent | Product, CX, and voice-of-customer teams |
| **What it reads** | Agent conversations, tool calls, traces, events | Customer feedback: tickets, calls, reviews, surveys, community, AI agent conversations |
| **How data arrives** | Python, TypeScript, and Go SDKs, OpenTelemetry, 12 agent frameworks, voice platforms | Connectors (Zendesk, Intercom, Salesforce, Gong, Decagon, and more), webhook, CSV |
| **Tool calls and agent internals** | Yes: tool success rate, errors, latency, spans | Not ingested |
| **Grouping** | Intents you name in plain language, with suggestions from your traffic | Adaptive taxonomy that updates as new themes appear |
| **Rule checks** | Natural-language rules checked per conversation, with evidence | Not a stated feature |
| **Business context** | Metadata filters you send (plan, cohort, agent version) | Customer context graph linking themes to accounts, segments, and revenue |
| **Alerts** | Email or Slack on intent or rule thresholds; daily and new-intent summaries | Slack monitors, including a quality monitor for AI-handled conversations |
| **From finding to fix** | Auto Improve tests a change against past runs and opens a PR | Enterpret Agent files tickets and hands fixes to product teams and coding agents |
| **Query from AI clients** | Hosted MCP server (Claude, Codex, Cursor), Slack agent, REST API | MCP access from Claude, Cursor, Codex, and ChatGPT |
| **Pricing** | Free (1,000 events/mo); $49 and $499/mo; Enterprise custom | Not published; sales-led |
| **Self-hosting** | Self-hosted VPC on Enterprise; not open source | Not offered on the pages we reviewed; enterprise data-residency options |


## Where Enterpret is stronger

- **Every feedback channel in one place.** Enterpret unifies support tickets, sales and support calls, app reviews, surveys, community posts, and AI agent conversations. Agnost AI only sees what your agent sends it.
- **Revenue context.** Its customer context graph ties each theme to accounts, segments, revenue, and releases, so a request can be weighted by ARR. Agnost AI filters by the metadata you send but does not model accounts or revenue.
- **Support-platform agents.** If your AI agent runs inside a support platform such as Decagon, Intercom, or Zendesk, Enterpret's connectors bring those conversations in without instrumenting code.
- **Voice-of-customer programs.** Weekly VoC reports, launch-feedback monitors, and escalation monitors are built for product and CX leaders rather than engineers.

## Where Agnost AI is stronger

- **Your agent's internals.** Agnost AI ingests tool calls and traces next to the conversation, so you can see that a user gave up right after a tool returned an empty result. Enterpret mentions no SDK, trace, or OpenTelemetry path.
- **Rules written as sentences.** [Violations](https://docs.agnost.ai/using-violations) check each analyzed conversation against rules such as "confirm identity before exposing account information" and report a violation rate with the supporting messages.
- **Developer setup.** Python, TypeScript, and Go SDKs, a hosted [OpenTelemetry endpoint](https://docs.agnost.ai/otel) that can sit next to your existing exporter, and integrations for LiveKit, Vapi, Retell, Telnyx, and Trellus voice agents.
- **A path from finding to pull request.** [Auto Improve](https://docs.agnost.ai/using-improvements) investigates a recurring finding, gathers repository context, prepares a change, tests it against past runs, and opens a pull request for your team to review.
- **Self-serve pricing.** Agnost AI has a free plan and published paid tiers. Enterpret does not publish prices.

## Using both together

They read different data, so running both is coherent rather than redundant. A common split: Agnost AI receives your agent's traces through the SDK or OpenTelemetry and drives agent fixes, while Enterpret stays on the feedback channels, including the agent's conversations if they already flow through Zendesk, Intercom, or Decagon. Most smaller teams that build their own agent start with one: Agnost AI if the agent is the product, Enterpret if the agent is one support channel among many.

## How to choose

| If your team… | Start with |
|---|---|
| Builds its own agent and wants to see where it fails users, with fixes as PRs | Agnost AI |
| Needs tool-call and trace evidence next to each conversation | Agnost AI |
| Runs an AI support agent inside Decagon, Intercom, or Zendesk and analyzes it with other feedback | Enterpret |
| Wants feature requests weighted by account revenue across every channel | Enterpret |
| Has both an in-house agent and a voice-of-customer program | Both, on their own data |

## Related reading

- [Best conversation analytics tools for AI agents (2026)](/blog/best-conversation-analytics-tools-ai-agents/)
- [How to extract feature requests from chatbot conversations](/blog/find-hidden-feature-requests-conversations/)
- [Agnost AI vs Langfuse](/blog/agnost-vs-langfuse/)
- [Conversation analytics tools for product teams: how to choose](/blog/conversation-analytics-tools-product-teams/)

To try Agnost AI on your own agent, start with the [quickstart](https://docs.agnost.ai/quickstart).

## Frequently asked questions

### What is the difference between Agnost AI and Enterpret?

Enterpret is customer-feedback intelligence: it unifies tickets, calls, reviews, surveys, and AI agent conversations into one taxonomy linked to accounts and revenue. Agnost AI is analytics for the agent itself: it ingests your agent's conversations, tool calls, and traces through an SDK or OpenTelemetry, classifies them against intents and rules, and turns recurring failures into pull requests.

### Can Enterpret analyze my AI agent's conversations?

Yes, as a feedback source. Enterpret ingests AI agent and support conversations through connectors such as Decagon, Intercom, and Zendesk, or a webhook. It does not mention SDK, trace, or OpenTelemetry ingestion, so tool calls and agent internals are outside what it analyzes.

### Which is better for finding feature requests in chatbot conversations?

If the requests are spread across tickets, calls, reviews, and agent chats, Enterpret, because it groups them in one place by feature, segment, and account revenue. If the requests surface inside your own agent and you want to see the turn and tool call where the agent could not help, Agnost AI.

### How much do Enterpret and Agnost AI cost?

Enterpret does not publish prices; it is sales-led with a demo or trial request. Agnost AI is free for 1,000 events a month, $49 a month for 10,000 events, $499 a month for 1,000,000 events, and custom on Enterprise.

### Can I self-host Agnost AI or Enterpret?

Agnost AI offers a self-hosted VPC deployment on its Enterprise plan; it is not open source. Enterpret mentions enterprise data-residency options but no self-hosted deployment on the pages we reviewed.