AgentMark

$59/mStarting price

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About AgentMark

AgentMark is a web platform and open-core SDK designed for developers and AI teams who need to build, test, and monitor AI agents in production using the same reliability practices as traditional software. The tool centralizes prompt, dataset, and evaluation management by storing prompts (MDX, Markdown + JSX) and datasets (JSONL) directly in a team’s GitHub repository, enabling auditable changes and seamless integration with CI workflows. Pre-deploy evaluations run in CI pipelines to catch regressions before they reach production, ensuring consistent agent performance. Production observability is provided through OpenTelemetry (OTLP), capturing detailed traces, spans, token usage, tool calls, and metrics such as cost, latency, and error rates. Alerts and diagnostics notify teams when quality, cost, or latency thresholds are breached, linking incidents back to specific prompt or model changes for faster debugging. The platform avoids proprietary SDK lock-in by leveraging Git for version control and standard OpenTelemetry for observability, while keeping prompts and evaluations as editable files within an existing codebase. The core SDK and prompt format are MIT-licensed on GitHub, with additional cloud features including multi-user access, managed storage, alerting, and hosted observability available in paid plans.

Key features

Git-backed prompt and dataset management
Pre-deploy CI evaluations for regression testing
OpenTelemetry-based production observability
Real-time alerts for quality, cost, or latency issues
MIT-licensed core SDK and prompt format
Multi-user access and managed cloud storage
Hosted observability and alerting
Integration with GitHub for version control
Token usage, cost, and latency tracking
Link incidents to specific prompt or model changes

Use cases

Monitoring AI agent performance in production
Debugging regressions with CI evaluations
Tracking token usage, cost, and latency metrics

Pros

Centralizes prompt, dataset, and evaluation management in GitHub for version-controlled changes
Supports pre-deploy evaluations in CI pipelines to catch regressions before production
Provides production observability via OpenTelemetry with detailed traces, spans, and metrics
Avoids proprietary SDK lock-in by using Git for version control and standard OpenTelemetry
Offers core SDK and prompt format under MIT license for open-source flexibility

Cons

Paid plans required for advanced features like multi-user access and managed storage
Learning curve for teams unfamiliar with Git-based workflows or OpenTelemetry integration
Limited documentation or examples for complex debugging scenarios

Frequently asked questions about AgentMark

What is AgentMark and who is it designed for?

AgentMark is a web platform and open-core SDK designed for developers and AI teams to build, test, and monitor AI agents in production. It provides tools for prompt, dataset, and evaluation management, enabling reliable AI agent development with practices similar to traditional software.

How does AgentMark integrate with existing workflows?

AgentMark stores prompts and datasets directly in a team’s GitHub repository, allowing auditable changes and seamless integration with CI workflows. Pre-deploy evaluations run in CI pipelines to catch regressions before they reach production.

What kind of observability does AgentMark provide?

AgentMark offers production observability through OpenTelemetry (OTLP), capturing detailed traces, spans, token usage, tool calls, and metrics such as cost, latency, and error rates. Alerts and diagnostics notify teams when quality, cost, or latency thresholds are breached.

Does AgentMark use proprietary formats or lock-in?

No, AgentMark avoids proprietary SDK lock-in by leveraging Git for version control and standard OpenTelemetry for observability. Prompts and evaluations are stored as editable files within an existing codebase.

What licensing model does AgentMark use?

The core SDK and prompt format are MIT-licensed on GitHub, while additional cloud features such as multi-user access, managed storage, alerting, and hosted observability are available in paid plans.

How can I get started with AgentMark?

Teams can begin by integrating AgentMark into their GitHub repositories to manage prompts and datasets. Pre-deploy evaluations can be set up in CI pipelines, and production observability can be configured using OpenTelemetry.