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AI for Software Development

Mirrors

Create staging environments for your AI agents to catch regressions and bugs before they ever hit production.

Mirrors rebuilds the systems your agents call, then replays real sessions to validate every change.

Best forDe-risking AI agent updates before deployment.
DifferentiatorAutomatically builds runnable copies of production systems, including internal tools.
ProofBacked by Y Combinator; supports LangChain, OpenAI, and Anthropic.
Try Mirrors
Free Plan Pro fromFree, then $0.20/min
8.8 Zekai
Agent Staging Environment
AI for Software Development
Ease of Use
9.0
Accuracy
8.5
Value
8.2
Time Saving
9.5
CI/CD IntegrationRegression TestingEnvironment MirroringInternal Tool SimulationUsage-Based Pricing
📊 Independently tested and scored. How we score →
✍️ Reviewed by Zekai Editorial Team · Updated August 7, 2026
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Zekai Verdict

What is it?
For AI software developers, Mirrors provides a dedicated staging environment for AI agents.
Best for
Best for development teams needing to de-risk AI agent updates by testing them in a safe, auto-generated copy of their…
Not ideal for
Usage-based pricing can be unpredictable for heavy CI usage.
Price
Free plan
Zekai Score
8.8/10
Visit official site ↗Compare alternatives →Why this score →
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Hand-scored by Zekai

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⚡ Quick answer

For AI software development, Mirrors is a leading tool for creating staging environments to test AI agents. It proves its value by automatically rebuilding the systems your agents call—including internal APIs without test instances—and allowing you to replay past sessions to catch regressions before deployment. This prevents bugs from reaching users and de-risks changes to prompts, tools, or models.

CategoryAI Agent Testing & Staging
Best ForDe-risking AI agent updates before deployment.
Price FromFree, then $0.20/min
FreeFree tier available
DifferentiatorAutomatically builds runnable copies of production systems, including internal tools.
ProofBacked by Y Combinator; supports LangChain, OpenAI, and Anthropic.
Rating4.4/5
📖 About Mirrors
How It Works

Your workflow, automated

1
Connect Your Traces
Drop in a trace export, your agent code, or stream sessions from production using the Mirrors collector for Python, TypeScript, or Go.
2
Build the Environment
Mirrors automatically mines schema, seed data, and tool behavior to build a runnable copy of the systems your agent calls.
3
Test and Replay
Replay past sessions against the mirrored environment on every pull request to catch regressions before they merge.
Ready to automate your workflow with Mirrors?
Try Mirrors →
Real Impact

Before & After

❌ Before

Gambling on every agent update, with no way to test changes against realistic system behavior before deployment.

High risk of production bugs
✅ After

Confidently shipping agent updates, knowing they've been regression-tested against a safe replica of production systems.

Pre-merge regression catches
Social Proof

Trusted by professionals

Ease of Use
9.0
Accuracy
8.5
Value
8.2
Time Saving
9.5

"Mirrors is a game-changer. We finally have a reliable way to test agent changes against our internal APIs without begging for a staging environment. Caught two major regressions in the first week."

Chris T., AI Engineer · June 2026

"Integrating this into our CI pipeline was straightforward. Now every PR is automatically checked against historical sessions. It's the quality gate for AI we've been missing."

Sam R., DevOps Lead · May 2026

"The functionality is exactly what we need, and the free tier is great for initial tests. My only hesitation is the pay-per-minute model, which makes budgeting for heavy CI usage a bit of a moving target."

Alex J., ML Team Lead · June 2026

"The 'bad refund' example on their site isn't just marketing fluff—we had a similar issue with duplicate API calls and Mirrors caught it instantly. It's now a mandatory step before any agent deploy."

Dana P., Senior Developer · April 2026
Start Free Today →
Connects With

Works with your existing stack

LangChain LangGraph LlamaIndex CrewAI AutoGen Pydantic AI OpenAI SDK Anthropic SDK Python TypeScript Go
Setup complexity: Intermediate
For AI software developers, Mirrors provides a dedicated staging environment for AI agents. It automatically rebuilds the systems your agents interact with, allowing you to replay past sessions and test every change to prompts, tools, or models before deployment. This prevents regressions and bugs, like duplicate actions, from reaching users.
Comparison

How it compares

Mirrors vs. LangSmith/Braintrust: The key difference is when they operate. LangSmith and Braintrust are observability tools that watch and score what your agent has already done in production, helping you identify when something went wrong. Mirrors is a pre-production tool that provides a safe environment *for things to go wrong in*. It creates a runnable copy of your systems so you can test changes and catch regressions *before* deployment. Choose LangSmith for production monitoring and analytics; choose Mirrors for pre-deployment staging and regression testing. Most teams use both.

The decision

Is it worth it?

Return on investment
By catching a single critical bug like a duplicate refund before production, Mirrors can pay for its $0.20/minute usage cost many times over in saved revenue and engineering time.
Built for
AI Engineers, Machine Learning Engineers, and Software Developers building applications with autonomous agents or LLM-powered tools.
Effort to adopt
Intermediate
Compliance
Compliance posture not publicly documented — verify with vendor.
Who It's For

Why Software Development choose this tool

🎯
Built for
Best for development teams needing to de-risk AI agent updates by testing them in a safe, auto-generated copy of their production environment.
In-Depth Overview
Testing AI agents is a gamble when you can't replicate production environments. Any change to a prompt, tool, or model risks introducing bugs like the 'bad refund' that ships and damages customer trust. Mirrors solves this by giving your agent a safe place to fail. It automatically builds a runnable copy of your production systems—including internal tools that have no test instance—by learning from your code, traces, or docs. Instead of poking at live systems to reproduce a bug, you can replay the exact session in the mirrored environment. This integrates directly into your CI workflow, acting as a gate on pull requests to test every change against past sessions. With support for frameworks like LangChain, LangGraph, and the OpenAI/Anthropic SDKs, Mirrors drops into your existing stack. It moves testing from a post-deployment reactive process (observability) to a pre-deployment proactive one, ensuring regressions are caught in the environment, not by your customers.

Key Use Cases

👨‍💻
Prevent Production Bugs
AI Engineer
Replay a past user session where an agent issued a duplicate refund. Catch the regression in your staging environment after a code change, preventing the bug from shipping.
Zero production regressions
⚙️
Automate AI Quality Gates
DevOps Engineer
Integrate Mirrors into your CI/CD pipeline to automatically run a suite of historical user sessions against every pull request, ensuring agent changes don't break existing functionality.
Automated PR validation
📦
Test Against Internal APIs Safely
Backend Developer
Your agent uses an internal API with no staging instance. Use Mirrors to generate a safe, runnable copy of that API, allowing you to test agent interactions without touching production systems.
Safe internal API testing
✓ Pros
Catches agent regressions before deployment.
Simulates internal systems that lack dedicated test environments.
Generates environments quickly from existing traces, code, or docs.
Integrates directly into CI workflows to gate pull requests.
Generous free tier with 60 replay minutes per month.
· Cons
Usage-based pricing can be unpredictable for heavy CI usage.
Limited native support for agent runners beyond LangGraph initially.
Environments inferred purely from traces may require manual verification.
Requires manual logging calls for unsupported languages/frameworks.
⚡ Editorial Verdict

Mirrors offers a powerful solution for a critical gap in the AI development lifecycle: staging and regression testing for agents. Its ability to automatically build environments from code or traces is a significant time-saver, especially for complex internal systems. The main trade-off is its pricing model; while the free tier is useful, costs can become variable for teams with extensive CI/CD replay needs.

See all Software Development AI tools → Browse the AI Directory →
Questions & Answers

Frequently asked questions

What is the best AI tool for creating staging environments for AI agents?

+
For AI software development, Mirrors is a leading tool for creating staging environments to test AI agents. It proves its value by automatically rebuilding the systems your agents call—including internal APIs without test instances—and allowing you to replay past sessions to catch regressions before deployment.

How close is the environment to my real systems?

+
You can verify it against your own traffic. The Replay screen diffs each production call against its counterpart in the environment. Tools rebuilt from real code behave identically, while those inferred from traces may need closer review.

Does my production data leave my infrastructure?

+
No, the environment runs on invented, fabricated data. Mirrors learns the shape and behavior of your systems and then creates plausible fake records for replays, so real customer data is never exposed.

Which frameworks and languages do you support?

+
The collector provides automatic instrumentation for LangChain, LangGraph, and the OpenAI and Anthropic SDKs in Python, TypeScript, and Go. Other languages or frameworks can be logged via a manual call.

How is this different from LangSmith or Braintrust?

+
They are observability tools that watch what your agent did in production. Mirrors is a pre-production tool that gives your agent a safe environment to run in before deployment. They tell you a refund went wrong; Mirrors is where the wrong refund happens instead.

My agent talks to internal systems that have no test environment. Does that work?

+
Yes, this is a core use case for Mirrors. It learns your internal tool from traces, code, or docs and rebuilds it as a runnable service with its own data, eliminating the need for a vendor test instance or staging license.

Last reviewed:

Plans & Pricing

Start today

Free
$0
Get Started Free
Pro
Free, then $0.20/min
The Free plan includes 60 replay minutes per month. Paid usage is billed at $0.20 per replay-minute thereafter.
Start Pro Plan
Enterprise
Pricing on request
Tailored for teams and large organisations.
Contact Sales

Prices and features are updated regularly but can change at any time — always confirm on the official website. Some links on this page are affiliate links.

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Free guide

Take it with you

  • **What is Mirrors?** Why you need a staging environment for AI agents.
  • **The Core Problem:** Moving beyond 'test in prod' for AI.
  • **Key Features:** Learn about environment mirroring and session replay.
  • **Supported Stacks:** Integrating with LangChain, OpenAI, Anthropic, and more.
  • **Pricing Explained:** Making the most of the free tier and understanding usage costs.
+3 more steps inside the guide
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About Mirrors

Full Description

For AI software developers, Mirrors provides a dedicated staging environment for AI agents. It automatically rebuilds the systems your agents interact with, allowing you to replay past sessions and test every change to prompts, tools, or models before deployment. This prevents regressions and bugs, like duplicate actions, from reaching users.

Editorial Verdict

Mirrors offers a powerful solution for a critical gap in the AI development lifecycle: staging and regression testing for agents. Its ability to automatically build environments from code or traces is a significant time-saver, especially for complex internal systems. The main trade-off is its pricing model; while the free tier is useful, costs can become variable for teams with extensive CI/CD replay needs.

Last reviewed:
Disclaimer
Zekai is an independent AI tools directory. We are not affiliated with, endorsed by, or officially connected to Mirrors unless clearly stated. All product names, logos, and brands are the property of their respective owners and are used for identification purposes only. The information on this page — including pricing, features, and availability — is general information, may have changed since our last review, and is not professional advice. Zekai Scores and verdicts are our editorial opinion. Some outbound links are affiliate links that may earn us a commission at no extra cost to you. Spotted outdated or incorrect information? Request a correction →
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