Tech Agent|From the Solo plan

An AI agent for your engineering team

The EzyAgents Tech agent works at a real workstation: an isolated terminal where it clones your GitHub repositories, reproduces the error before concluding, runs your tests and shows the actual output. It audits the security of your code, reviews your changes, writes your runbooks and follows your incidents from opening to post-mortem.

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Conclusions verified, not guessed

Whatever can be run, is run: the agent reproduces the problem in the sandbox and always separates what it observed from what it assumes.

  • Security audit of your GitHub repositories: code flaws, committed secrets, vulnerable dependencies, workflows and GitHub settings
  • Repositories cloned into an isolated terminal: problem reproduced, tests run, real output

Flaws found before the attackers

Code, secret and dependency scanners, then a manual review by category (authentication, injections, data exposure, CI/CD): every finding has a file, a severity and a fix.

  • Changes proposed as pull requests, after your tests and a human approval
  • Scripts written and then run on sample data, with the real output shown

Incidents followed end to end

Severity assessed, ticket opened, the channel updated at the right cadence, the root-cause analysis kept current, post-mortem placed in the calendar.

  • Code reviews in priority order: correctness, security, performance, readability
  • Runbooks, architecture notes and post-mortems kept as living documents

Documentation that does not go stale

Runbooks, architecture notes and root-cause analyses are living documents, updated as things change rather than duplicated.

  • Incidents graded by severity, tickets opened and tracked, the team informed in Slack or Teams
  • Watch on your technical stack: versions, published vulnerabilities, tooling choices

What the agent takes care of

It does not touch your production. Its changes reach you as a pull request, approved by a person before it leaves; the commands that act on your systems are still run by a human, and tickets and emails go out only after approval.

  • Security audit of your GitHub repositories: code flaws, committed secrets, vulnerable dependencies, workflows and GitHub settings
  • Repositories cloned into an isolated terminal: problem reproduced, tests run, real output
  • Changes proposed as pull requests, after your tests and a human approval
  • Scripts written and then run on sample data, with the real output shown
  • Code reviews in priority order: correctness, security, performance, readability
  • Runbooks, architecture notes and post-mortems kept as living documents
  • Incidents graded by severity, tickets opened and tracked, the team informed in Slack or Teams
  • Watch on your technical stack: versions, published vulnerabilities, tooling choices
GmailGmailOutlookOutlookSlackSlackMicrosoft TeamsMicrosoft TeamsJiraJiraGitHubGitHubGoogle DriveGoogle DriveServeurs MCP

Frequently asked questions

Yes. The Tech agent has an isolated Python sandbox: it installs its dependencies there, runs the script and shows you the output. In other languages it reasons, but states explicitly that its conclusion was not executed.

The agent clones the repository into its isolated terminal and runs recognised scanners (semgrep for code, gitleaks for secrets, osv-scanner for dependencies), then reviews the code by category: authentication, authorization, injections, data exposure, cryptography, CI/CD, infrastructure. On the GitHub side it checks branch protection and Dependabot alerts. You get a report with severity, file, impact and fix for every finding, tickets for the urgent ones, and the audit can be replayed every month.

No, by design. It works on a copy of your code in an isolated sandbox; its changes reach you as a pull request, never on the main branch, and a person approves them before they leave. It reads status pages and consoles, prepares the commands and documents them; running them on your systems is left to a human.

It grades the severity, opens the tracking ticket, updates Slack or Teams at the cadence set for that level, keeps the root-cause analysis current as the investigation progresses, then schedules the post-mortem in the calendar once the incident is resolved. A mailbox dedicated to alerts can be triaged at fixed times.

Yes, through your MCP servers, your custom webhook tools and the API. The agent first lists what is actually connected: it never invents a server or a tool name. Read calls run freely, writes follow your approval rules.

Get started

14-day free trial, no credit card. Live in 10 minutes.

01

Create your workspace

An email is enough. Your Manager and first agents are ready in minutes.

02

Connect your tools

Gmail, HubSpot, Slack, Pennylane: one click per connector, no API key.

03

Hand over a first mission

To the Manager or to an agent. You approve what goes out, it does the rest.

Start for freeSee pricing

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