• Combines AI observability with Sentry's existing error monitoring, tracing, logs, dashboards, and alerting, which is efficient for teams already using Sentry.
• Tracks agent runs, LLM calls, error rates, token usage, tool executions, traffic patterns, and duration metrics from one monitoring environment when instrumentation is configured.
• Provides cost and token visibility by model where supported by the relevant SDK and telemetry configuration.
• Supports trace-level debugging with AI spans, agent invocations, tool executions, token counts, costs, timing, and configurable prompt and response context.
• Has documented setup paths for Python OpenAI Agents and JavaScript Vercel AI SDK instrumentation, plus Sentry SDK coverage for common application stacks.
• Business and Enterprise plans add operational controls such as quota management, SAML/SCIM support, longer lookback, and dedicated support options where included in the selected plan.

⚠️ Consider This

• Most compelling for existing Sentry customers; teams not already using Sentry may need to adopt a broader observability platform just to get AI monitoring.
• Total cost can rise with usage-based telemetry such as errors, spans, logs, replays, and attachments, so headline plan prices may not reflect real production spend.
• Seer, Sentry's AI debugging agent, is priced separately at $40 per active contributor per month on Team and Business, which can add materially to team cost.
• Dedicated LLM observability platforms may be a better fit for teams that want an AI-first product focused only on prompts, evaluations, datasets, and model experimentation.
• Enterprise pricing is custom, so larger organizations will need a sales process to understand exact costs and contractual terms.

What Users Say About Sentry AI Monitoring

👍 What Users Love

✓Combines AI observability with Sentry's existing error monitoring, tracing, logs, dashboards, and alerting, which is efficient for teams already using Sentry.
✓Tracks agent runs, LLM calls, error rates, token usage, tool executions, traffic patterns, and duration metrics from one monitoring environment when instrumentation is configured.
✓Provides cost and token visibility by model where supported by the relevant SDK and telemetry configuration.
✓Supports trace-level debugging with AI spans, agent invocations, tool executions, token counts, costs, timing, and configurable prompt and response context.
✓Has documented setup paths for Python OpenAI Agents and JavaScript Vercel AI SDK instrumentation, plus Sentry SDK coverage for common application stacks.
✓Business and Enterprise plans add operational controls such as quota management, SAML/SCIM support, longer lookback, and dedicated support options where included in the selected plan.

👎 Common Concerns

⚠Most compelling for existing Sentry customers; teams not already using Sentry may need to adopt a broader observability platform just to get AI monitoring.
⚠Total cost can rise with usage-based telemetry such as errors, spans, logs, replays, and attachments, so headline plan prices may not reflect real production spend.
⚠Seer, Sentry's AI debugging agent, is priced separately at $40 per active contributor per month on Team and Business, which can add materially to team cost.
⚠Dedicated LLM observability platforms may be a better fit for teams that want an AI-first product focused only on prompts, evaluations, datasets, and model experimentation.
⚠Enterprise pricing is custom, so larger organizations will need a sales process to understand exact costs and contractual terms.

Pricing FAQ

What does Sentry AI Monitoring track?

It tracks AI and LLM observability signals such as agent runs, LLM calls, error rates, token usage, tool executions, traffic patterns, duration, and trace context when the application is instrumented.

Is Sentry AI Monitoring only for LLM calls?

No. Sentry presents it as observability for agents, LLMs, vector stores, tools, and custom application logic, with emphasis on production debugging across the whole AI workflow.

Which AI frameworks does Sentry document for setup?

The public AI observability page shows setup examples for Python OpenAI Agents through OpenAIAgentsIntegration and JavaScript Vercel AI SDK instrumentation.

Can Sentry show prompts and responses?

Sentry describes prompt and response context as part of deep trace analysis, but teams should confirm SDK behavior, defaults, and privacy configuration before collecting prompt or response content.

Is Seer the same thing as Sentry AI Monitoring?

No. Sentry AI Monitoring refers to AI and LLM observability for production behavior. Seer is Sentry's AI debugging agent for root cause analysis, fix generation, and related debugging assistance.

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Pricing sourced from Sentry AI Monitoring · Last verified March 2026

Is Sentry AI Monitoring Worth It?

✅ Why Choose Sentry AI Monitoring

• Combines AI observability with Sentry's existing error monitoring, tracing, logs, dashboards, and alerting, which is efficient for teams already using Sentry.
• Tracks agent runs, LLM calls, error rates, token usage, tool executions, traffic patterns, and duration metrics from one monitoring environment when instrumentation is configured.
• Provides cost and token visibility by model where supported by the relevant SDK and telemetry configuration.
• Supports trace-level debugging with AI spans, agent invocations, tool executions, token counts, costs, timing, and configurable prompt and response context.
• Has documented setup paths for Python OpenAI Agents and JavaScript Vercel AI SDK instrumentation, plus Sentry SDK coverage for common application stacks.
• Business and Enterprise plans add operational controls such as quota management, SAML/SCIM support, longer lookback, and dedicated support options where included in the selected plan.

⚠️ Consider This

• Most compelling for existing Sentry customers; teams not already using Sentry may need to adopt a broader observability platform just to get AI monitoring.
• Total cost can rise with usage-based telemetry such as errors, spans, logs, replays, and attachments, so headline plan prices may not reflect real production spend.
• Seer, Sentry's AI debugging agent, is priced separately at $40 per active contributor per month on Team and Business, which can add materially to team cost.
• Dedicated LLM observability platforms may be a better fit for teams that want an AI-first product focused only on prompts, evaluations, datasets, and model experimentation.
• Enterprise pricing is custom, so larger organizations will need a sales process to understand exact costs and contractual terms.

What Users Say About Sentry AI Monitoring

👍 What Users Love

✓Combines AI observability with Sentry's existing error monitoring, tracing, logs, dashboards, and alerting, which is efficient for teams already using Sentry.
✓Tracks agent runs, LLM calls, error rates, token usage, tool executions, traffic patterns, and duration metrics from one monitoring environment when instrumentation is configured.
✓Provides cost and token visibility by model where supported by the relevant SDK and telemetry configuration.
✓Supports trace-level debugging with AI spans, agent invocations, tool executions, token counts, costs, timing, and configurable prompt and response context.
✓Has documented setup paths for Python OpenAI Agents and JavaScript Vercel AI SDK instrumentation, plus Sentry SDK coverage for common application stacks.
✓Business and Enterprise plans add operational controls such as quota management, SAML/SCIM support, longer lookback, and dedicated support options where included in the selected plan.

👎 Common Concerns

⚠Most compelling for existing Sentry customers; teams not already using Sentry may need to adopt a broader observability platform just to get AI monitoring.
⚠Total cost can rise with usage-based telemetry such as errors, spans, logs, replays, and attachments, so headline plan prices may not reflect real production spend.
⚠Seer, Sentry's AI debugging agent, is priced separately at $40 per active contributor per month on Team and Business, which can add materially to team cost.
⚠Dedicated LLM observability platforms may be a better fit for teams that want an AI-first product focused only on prompts, evaluations, datasets, and model experimentation.
⚠Enterprise pricing is custom, so larger organizations will need a sales process to understand exact costs and contractual terms.

Pricing FAQ

What does Sentry AI Monitoring track?

Is Sentry AI Monitoring only for LLM calls?

No. Sentry presents it as observability for agents, LLMs, vector stores, tools, and custom application logic, with emphasis on production debugging across the whole AI workflow.

Which AI frameworks does Sentry document for setup?

The public AI observability page shows setup examples for Python OpenAI Agents through OpenAIAgentsIntegration and JavaScript Vercel AI SDK instrumentation.

Can Sentry show prompts and responses?

Sentry describes prompt and response context as part of deep trace analysis, but teams should confirm SDK behavior, defaults, and privacy configuration before collecting prompt or response content.

Is Seer the same thing as Sentry AI Monitoring?

No. Sentry AI Monitoring refers to AI and LLM observability for production behavior. Seer is Sentry's AI debugging agent for root cause analysis, fix generation, and related debugging assistance.