AI that analyzes your session replays to uncover issues and behavior

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June 7, 2024

Decipher

United States Decipher AI Debugging

4,959

3.5(2)

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4,959

3.5(2)

AI that analyzes your session replays to uncover issues and behavior

Session Replays AI Bug Detection Bug Fixing Error Monitoring AI-Assisted Debugging Session Replay AnalysisFree + from $199/mo

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Decipher is a next-gen Sentry replacement that helps you uncover, prioritize, and debug production issues faster.

Real Product Impact
Decipher determined the real product impact using session replays, code, and error data so you can prioritize and map them to support tickets.

Intelligent Alerting
Decipher's AI distinguishes critical issues from noise, ensuring you only receive alerts that demand your attention. No fussy filters or thresholds required.

Smart Grouping
Decipher automatically clusters related errors, giving you a clear overview of issues affecting your product. The first actually useful error dashboard.

Issue Insights
Decipher reveals patterns and insights across every instance of the same error by analyzing all shared attributes - including requests, logs, and local variables.

AI Debugging
Decipher's AI uses codebase wide understanding and product context to root cause bugs. It can help you get started or even submit a pull request.

Customer Reports, Correlated
Decipher automatically correlates support tickets with relevant errors, bridging the gap between customer reports and monitoring.

Releases

DecipherInitial

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Initial release

May 8, 2024

Initial release of Decipher.

Author

Michael Rosenfield

@michaelrosenfie-21818079-1720050919

Company

Decipher AI

🇺🇸 United States

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1 tool

Beginner

Joined: July 2024

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Freemium

Paid options from

$199/month

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Monthly

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United States Decipher AI Debugging

4,959

3.5(2)

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Pros and Cons

Pros

Error cause ascertainment

User impact analysis

Provides bug resolution methodologies

Captures logs for debugging

Captures request bodies for debugging

Captures local variables for debugging

Analysis of session replays

Assessment of runtime data

Source code evaluated

Generates high-signal bug alerts

Uses system-wide runtime data

Compatible with Next.js

Supports Flask framework

Supports FastAPI framework

Supports Express framework

Easy quick-start with few lines of code

Debugs issues automatically

Investigates root cause of bugs

Prioritizes bugs based on analysis

Impactful production monitoring

Includes all needed debugging context

Allows fast debugging

Setup in minutes

Easy SDK installation

Unlocks fast bug fixes

Reproduces and debugs issues

Presents entire stack trace

Provides comprehensive request data

Compiles viable debugging logs

Offers free version

Unlimited errors in paid version

Unlimited codebases in paid version

View 27 more pros

Cons

Limited framework compatibility

No standalone application

Requires adding code lines

Limited team members in Free plan

Free version: limited error notifications

Costly Pro and Business plans

No on-premises version

Limited number of codebases supported

View 3 more cons

Included in collections

Powerful tools for Coding

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Alexander Singh

Q&A

What makes Decipher different from other error monitoring platforms?

Differentiating Decipher from other error monitoring platforms is its AI-driven approach to bug detection and resolution. Decipher takes a step further by not only identifying the bugs but also ascertaining the error cause, user impact, and providing methodologies for bug resolution. All this without the need to manually trawl through error logs and code. It also supports session replay, which can help to understand exactly what a user did leading up to an error.

How does Decipher use AI to make bug detection and resolution more efficient?

Decipher uses artificial intelligence (AI) to analyze session replays and runtime data, which helps in efficient bug detection and resolution. The AI system can identify the root cause of each error, generate a user impact analysis and prioritize resolution methodologies based on these findings. It boosts the error monitoring accuracy by examining the source codes and enables teams to swiftly address issues by creating high-signal bug alerts.

What specific information does Decipher capture for debugging issues?

For debugging issues, Decipher captures exhaustive information including logs, request bodies, and local variables. This information is captured automatically once a few lines of code are incorporated into the system.

How does Decipher measure the actual user impact of a bug?

Decipher measures the actual user impact of a bug by analysing individual session replays, runtime data, and source code. This integrated investigation helps in determining the actual user impact of the bug, providing high-signal bug alerts for rapid response and fix.

What platforms and frameworks is Decipher compatible with?

Decipher is notably compatible with Next.js on the frontend. It also supports popular back-end frameworks including Flask, FastAPI, and Express, making it versatile for various system environments.

How easy is it to integrate Decipher into my existing system code?

Integrating Decipher into an existing system code is presented as a straightforward process. With just a few lines of code, Decipher can be embedded to capture all requisite information for debugging issues, making it a quick setup.

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How does Decipher use system-wide runtime data during its error monitoring process?

Decipher utilizes system-wide runtime data in its error monitoring process to identify errors and start an investigation into their root cause. The information aids Decipher in generating a summarized issue report, which is then used to prioritize and kickstart the bug resolution process.

What exactly is user impact analysis and how does Decipher generate it?

User impact analysis is an AI-generated review that Decipher produces for every error. This analysis outlines the impact an error has on the user experience. By examining session replays, runtime data and source code, Decipher develops a comprehensive understanding of how the bug affects users and prioritizes bug-fixes accordingly.

How does Decipher prioritize the process of bug resolution?

Decipher prioritizes bug resolution by using AI to identify and analyze errors, ascertain their cause, and measure their user impact. The bugs that have a higher impact on users are given a higher priority, which allows teams to focus on fixing the most critical issues first.

What are the high-signal bug alerts provided by Decipher?

High-signal bug alerts by Decipher are bug alerts that are generated by extensively analyzing relevant session replays, runtime data and source code. These alerts signify high-priority bugs that have substantial user impact, enabling teams to prioritize these over less critical bugs.

Can Decipher support the Express framework on the backend?

Yes, Decipher does support the Express framework on the backend. This makes it accommodative for different backend technologies and expands its usability.

How can I quick-start with Decipher in my company?

Companies can quick-start with Decipher by incorporating a few lines of system code, which allows Decipher to capture the necessary data for debugging. The process is designed to be straightforward, initiating AI-powered error monitoring and bug detection swiftly.

What methodologies does Decipher provide for bug resolution?

Decipher provides methodologies for bug resolution based on its comprehensive analysis of each error. After identifying an error, it ascertains its cause, measures its user impact, and based on these factors, recommends an effective solution or corrective action.

How does Decipher analyze session replays and runtime data?

Decipher employs AI to meticulously analyze session replays and runtime data. By doing so, it's able to understand user actions leading up to an error, identify patterns, detect anomalies, and ultimately discover bugs. This thorough analysis also helps in determining the actual impact of a bug on a user's session.

What factors determine the priority of a bug in Decipher?

The priority of a bug in Decipher is determined by the actual user impact, which is assessed through in-depth analysis of session replays, runtime data, and source code. Bugs that have higher user impact are given priority. This allows teams to efficiently address the most critical issues first.

Can Decipher identify the root cause of every error?

Decipher is designed to identify the root cause of every error. It achieves this by comprehensively analyzing system-wide runtime data, which helps it summarize each issue and begin an investigation into the root cause, thereby enabling swift and effective troubleshooting.

How does Decipher monitor and fix bugs with AI assistance?

Decipher monitors and fixes bugs with the help of AI by analyzing session replays and runtime data to identify errors and their causes. After an error is detected, Decipher ascertains its user impact, generates an issue summary and begins an investigation into the root cause, enabling an efficient bug resolution.

What role does Decipher's source code examination play in bug resolution?

Source code examination in Decipher plays a pivotal role in identifying bugs and understanding their impact on users. By scrutinizing the code, Decipher is able to detect anomalies that may be causing errors. This examination, along with session replay and runtime data analysis, contributes to comprehensive bug detection and resolution.

Do I need to set up anything on my end for Decipher's AI-Assisted Debugging to function?

For Decipher's AI-Assisted Debugging to function, a few lines of system code need to be incorporated. This action enables Decipher to capture all the required information for identifying and debugging issues. This setup is designed to be straightforward and easy.

Is there a trial period or demo available for new users of Decipher?

Yes, there is a trial period available for new users of Decipher. The 'Pro' subscription comes with a 30-day free trial. Users can also use the 'Free' plan which is indeed, free forever.

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