AI Tool

Hilma Review

Hilma is an AI-powered Pull Request (PR) scoring and decisioning tool that automates context gathering and impact analysis in software development workflows.

shipped Aug 14, 2026codefreemium

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Why it matters

1Hilma automates the evaluation of business logic, blast radius, and user impact of changes in pull requests.

2The platform leverages AI to analyze context and quantify risks associated with code changes across six core dimensions.

3Hilma is currently in private beta, with its company, Grundbulten 161704 AB, based in Stockholm, Sweden.

4It integrates with business tools such as GitHub, Jira, Linear, PostHog, Amplitude, Intercom, Dovetail, Notion, Confluence, and Slack.

About Hilma

Headquarters

Stockholm, Sweden

Pricing Plans

Request access

Screenshots

overview

What is Hilma?

Hilma is a AI-powered Pull Request (PR) scoring and decisioning tool developed by Grundbulten 161704 AB that enables developers, AI-assisted developers, and engineering teams to automate the evaluation of business logic, blast radius, and user impact of changes in pull requests before merging. It leverages AI to analyze context and quantify risks associated with code changes, aiming to eliminate the PR bottleneck by automating context gathering and impact analysis for code reviews.

features

Key Features of Hilma

Hilma provides a suite of features designed to streamline the pull request review process and enhance decision-making for engineering teams. These capabilities focus on AI-driven analysis and automation to improve efficiency and reduce risk in software development.

Automates evaluation of business logic in pull requests.
Automates evaluation of blast radius in pull requests.
Automates evaluation of user impact of changes in pull requests.
Leverages AI to analyze context and quantify risks across multiple dimensions.
Automatically evaluates PRs against business logic and user impact.
Integrates with existing business tools including GitHub, Jira, Linear, and PostHog.
Provides AI-assisted code review processes.
Enables auto-merging based on configurable evaluation scores and policy rules.
Offers intelligent routing and action recommendations for pull requests.
Facilitates AI-powered async standups and deep well-being insights for team culture.

use cases

Who Should Use Hilma?

Hilma is primarily designed for software development professionals and engineering teams seeking to optimize their pull request workflows and mitigate risks associated with code changes. Its AI-driven capabilities cater to specific roles and organizational needs within the software development lifecycle.

Developers: For automating context gathering and receiving AI-assisted analysis and scoring of pull requests.
AI-assisted Developers: To streamline the review process for AI-generated diffs and ensure business logic soundness.
Code Reviewers: For quantifying business and technical risk in pull requests and receiving intelligent routing and action recommendations.
Engineering Teams: For automating routine pull request merges based on defined policy rules and improving overall team well-being with async standups and wellness insights.

how to use

How to Use Hilma

Hilma is currently in private beta, requiring an invitation for access. Once access is granted, users can integrate Hilma with their existing development and business tools to begin automating pull request analysis.

1Request access to the private beta via the official Hilma website (gethilma.io).
2Upon invitation, connect Hilma to your version control system, such as GitHub.
3Integrate Hilma with relevant business tools like Jira, Linear, PostHog, and Slack.
4Configure policy rules for risk levels and auto-merging based on your team's requirements.
5Hilma will then automatically analyze pull requests, providing context, risk quantification, and action recommendations.
6Utilize the AI-powered insights for code reviews, routing decisions, and team well-being initiatives.

pricing

Hilma Pricing & Plans

Hilma operates on a freemium model. Specific pricing details for advanced tiers are not publicly disclosed due to its private beta status and require direct contact for access. The platform emphasizes enterprise-grade privacy and security measures.

Freemium: Free access with core functionalities.
Request access: Contact sales for information on advanced features and enterprise plans.

Pros

+Automates evaluation of business logic, blast radius, and user impact in pull requests.
+Leverages AI to quantify risks across six core business and technical dimensions.
+Integrates with a wide range of existing business tools including GitHub, Jira, and Slack.
+Offers intelligent routing and action recommendations for pull requests.
+Enables configurable auto-merging of routine changes based on policy rules.
+Provides AI-powered async standups and well-being insights for team culture.

Cons

−Currently in private beta, limiting public access and potentially subject to feature changes.
−Specific pricing details for advanced tiers are not publicly available, requiring direct contact.
−No public user reviews are widely available due to its private beta status.
−API is not currently available for external integration beyond its core platform.

Similar Tools

Hilma vs Competitors

Hilma positions itself as an AI reasoning layer for Pull Requests, differentiating itself by focusing on the evaluation of business logic, blast radius, and user impact, rather than solely on general code quality or test generation. This specialized approach aims to address the PR bottleneck caused by the increasing speed of AI-assisted development.

CodeRabbitOn Stork

Provides AI-powered code reviews, identifying issues, suggesting improvements, and explaining code changes directly in pull requests.

While CodeRabbit offers general AI code review and suggestions to improve code quality, Hilma specifically emphasizes evaluating 'business logic, blast radius, and user impact,' which might involve a more specialized AI model for contextual risk assessment.

CodiumAIOn Stork

Generates meaningful tests for code and suggests code improvements, helping developers ensure correctness and prevent regressions.

CodiumAI focuses on preventing issues by improving test coverage and code quality. Hilma, in contrast, directly analyzes the potential impact and risks of changes *before* they are merged, rather than primarily focusing on test generation.

SonarQube (Community Edition)On Stork

Provides comprehensive static analysis for code quality and security, identifying bugs, vulnerabilities, and code smells across many languages.

SonarQube offers robust static analysis to catch a wide range of code issues that could lead to negative impact. However, it relies on predefined rules and doesn't use AI to evaluate 'business logic, blast radius, and user impact' in the contextual, predictive way Hilma claims to.

DeepSourceOn Stork

Automates code review for various issues like bugs, performance, security, and anti-patterns, and can automatically fix some issues.

DeepSource provides automated code quality and security analysis, which helps reduce the likelihood of negative impact. Hilma's specific focus on AI-driven evaluation of 'business logic, blast radius, and user impact' offers a more targeted risk assessment beyond general code quality checks.

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