Everything inline does
inline starts with a review on every pull request and grows out from there: the tests, the merge, what your team has taught it, your coding agents, your security exposure and the systems around the code. Each part has its own page.
Code review
The review on every pull request, the tests behind it, the gate that holds the merge, and the memory that makes the next review better than the last.
The review
Line-anchored findings with a severity, a confidence and a validation pass behind them, from a review that reads the code around the diff.
Read moreSpecialist reviewers
Up to three specialists read a risky change for security, correctness, concurrency or API breakage, and a verifier tries to refute each finding before it posts.
Read moreSandbox tests
Dependencies installed, the suite run, tests written for uncovered code, and the terminal trace kept, in a sandbox built for each pull request.
Read moreWalkthroughs
A hosted, layered reading of a reviewed pull request: the diff reordered into layers that each say why they exist, behind a link on the pull request.
Read moreMerge gate
A check run on every pull request head that blocks at the severity you choose and opens on its own when threads resolve or a push fixes the code.
Read moreRepo memory
Outcomes harvested when a pull request closes, house rules with evidence, a profile of each repository and a wiki kept current on every push.
Read moreLearnings
Teach inline a rule from a pull request. It drafts rules from what your team dismisses and fixes, and retires the ones the evidence stops backing.
Read moreRepository wiki
A wiki generated from each repository and rebuilt on every push, plus a check that quotes the docs a merged pull request made wrong.
Read moreEngineering metrics
DORA figures, cycle time split by stage, and how much of the work an AI wrote, counted from the pull requests and deploys inline already sees.
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Fix and automate
The same reviewer before the pull request exists: in your coding agent, your terminal and your editor, reading the code through a graph instead of grep.
Coding agents
An MCP server any coding agent can call for a review before the pull request exists, and visual plans a person signs off before the agent writes code.
Read moreCLI and editors
Review staged changes from the terminal or your editor before a pull request exists, with the same reviewer the bot uses, and gate a push on it.
Read moreCode graph
A commit-anchored graph of symbols, calls and imports that the reviewer walks instead of grepping, following the real dependency closure of a change.
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Security and runtime
Advisories judged against your code, a red team that proves what it reports, the AI each repository ships, and the machines it all runs on.
Security
Advisories assessed for reachability in your code, malware alerts within minutes, remediation pull requests and an AI bill of materials per repository.
Read moreAI bill of materials
Every AI SDK, model identifier, MCP server and prompt in each repository, with the file and line, rebuilt on each scan and exported as CycloneDX.
Read morePentest
An engagement attacks one repository in an isolated sandbox and reports only the vulnerabilities it exploited, each with a proof of concept and its evidence.
Read moreFleet
One command enrolls a Linux, macOS or Windows machine. inline maps what can reach each port and proposes firewall plans that roll back unless confirmed.
Read moreAccess control
A module and action permission model where people, coding agents and share links are all principals, each with exactly the access its role grants.
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Platform
The cloud, the pipeline, the errors in production, the prompts in your code and the vendors it talks to, on the same console and models.
Cloud monitoring
Connect an Azure subscription with one pasted command and read-only roles. inline turns its posture, health and spend into a prioritized list of findings.
Read moreCI monitoring
A failed run gets a root-cause comment on the pull request that caused it. Flaky tests and builds slower than their baseline collect in one list.
Read moreRuntime errors
An SDK sends the crashes your users hit. inline groups them into one issue per bug, prioritizes each one and names the change that shipped it.
Read morePrompt evals
inline finds the LLM prompts in your repository, writes happy path, edge, adversarial and boundary cases for each, runs them and grades the answers.
Read moreCompliance
inline finds the providers your code sends data to, reads the agreements you signed, and raises a finding for each provider used without cover.
Read moreAutomations
Run a review, a comment, a coding session or a notification when a pull request opens, a check fails, a schedule fires or a signed webhook arrives.
Read moreSelf-hosting
Run inline in one container beside SQL Server, Redis and blob storage, configured from the environment, with models on your own cloud accounts.
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Put it on one repository
Connect GitHub or GitLab, enable a repo, and the next pull request opened gets a review.