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EntelligenceAIAI copilot for engineering teams: code review, security checks, and team insights.

4.8 (4)
Daniel NikulshynReviewed by Daniel Nikulshyn·Updated June 2026

Overview

EntelligenceAI is an AI copilot designed for engineering teams, aimed at enhancing production reliability. It achieves this by reviewing every pull request against past incidents, monitoring production live, and automatically resolving issues before the same failure occurs twice. EntelligenceAI's functionality is centered around three key components: code review, security checks, and team insights. In code review, the tool evaluates each diff against past incidents, highlighting potential issues and preventing the same class of bugs from shipping twice. The 'Agent Sessions' feature allows teams to identify problems early, often before alerts are triggered. Additionally, EntelligenceAI's 'Production Incidents' feature enables teams to search and recall past incident resolutions, leveraging this knowledge to improve future fixes. EntelligenceAI's research has also shed light on the economics of AI code spend, revealing that only 18% of AI dollar allocations actually ship, with the majority being used for bug fixing, rework, and review. The tool's incident resolution process is handled by 'Ellie', which deploys a set of agents to find the root cause, ship the fix, and verify it against history.

Key features

  • AI-assisted code review
  • Security vulnerability detection
  • Engineering team analytics
  • Workflow and repo integrations
  • Customizable review rules
  • Pull request automation

Pricing

Model
Free
Category
Productivity
Rating
4.8 / 5 (4)

Use cases

Automated Pull Request Reviews

Free senior engineers from routine review work by letting the AI copilot inspect pull requests, flag issues, and suggest improvements directly in the existing workflow.

Early Security Vulnerability Detection

Surface security and quality risks earlier in the development cycle so teams can address vulnerabilities before they reach production.

Engineering Team Visibility for Managers

Give engineering managers analytics on how teams are shipping work, helping them spot bottlenecks and track productivity patterns without disrupting delivery.

Enforcing Custom Code Standards

Define customizable review rules so every change is checked against team-specific standards, ensuring consistency across repositories and contributors.

Pros & Cons

Pros

  • Automates routine code review tasks
  • Highlights security and quality risks early
  • Provides team-level engineering insights
  • Fits into existing developer workflows

Cons

  • Effectiveness depends on codebase context
  • May require tuning to match team standards
  • Pricing not always transparent upfront

Reviews

4.8

Average from 4 ratings.

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A

Aisha Khan

Sep 1, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: pull request automation and highlights security and quality risks early. Where it lags: pricing not always transparent upfront. On balance the feature set — especially security vulnerability detection — justifies the 4 stars for our use case.

D

Daniel Schmidt

Aug 30, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is aI-assisted code review — handled better than most — and highlights security and quality risks early. Pricing not always transparent upfront is my one real gripe. Worth the time if this is your use case.

R

Robert Ainsworth

Aug 20, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: security vulnerability detection and fits into existing developer workflows. On balance the feature set — especially pull request automation — justifies the 5 stars for our use case.

I

Ingrid Bauer

Jun 24, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is workflow and repo integrations — handled better than most — and provides team-level engineering insights. Worth the time if this is your use case.

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