AI adoption can be a checkbox.
Or it can be a transformation.
The LiveReview 14-Day Transformation
Transform the business by transforming engineering.
Over two weeks, we help you establish a new engineering operating model:
- Safer reviews for critical changes
- Faster reviews for routine work
- Data-backed engineering decisions
- A measurable first step toward becoming an AI-native team
LiveReview works across your repositories and your engineering workflow, with four phases designed to change how your team reviews, ships, and improves software.
15
Days
4
Phases
30
Actions
2
Reports delivered
The four phases
Where you are going, and when
Support
How we support you through the program
The program is 14 working days, which is three calendar weeks for most teams. You get a direct line to our team throughout, and three scheduled sessions along the way.
Reach us any time
Every channel reaches the same engineers who set your instance up.
- Email us at [email protected].
- Discord: join the LiveReview community↗.
- Slack: invite us into a shared channel in your workspace, so answers arrive where your team already works. Microsoft Teams is supported the same way.
Scheduled sessions
One session at the end of each week, 30 minutes each. The first two are part of the program, the third is optional.
Week 1, Fridayafter days 1 to 5
Setup review
With the team that ran the installation. We confirm every provider is connected, reviews are reaching the right pull requests, and tune anything that is too noisy on the call.
Week 2, Fridayafter days 6 to 10
Adoption review
With the engineers using it daily. We look at what they act on, what they ignore, and which repository rules are worth writing down so reviews start matching your codebase.
Week 3, Fridayafter days 11 to 15
Results review with your leadership
We walk through your Impact Report together, so the numbers you take into a renewal or budget conversation are ones you can defend.
Book all three in week one at times that suit your team.
The shift
| Today | After two weeks |
|---|---|
×Repeated comments Senior engineers repeatedly point out the same issues in reviews. | ✓Reinforced standards Routine engineering practices are reinforced automatically, allowing reviewers to focus on architecture and design. |
×Late bug discovery Bugs are often discovered by QA, or worse, by customers. | ✓Earlier bug discovery More issues are caught while the developer is still working on the change. |
×Reviewer-dependent quality Engineering quality depends heavily on who reviewed the code. | ✓Consistent quality Teams begin following the same engineering practices regardless of reviewer. |
×Blind leadership Leadership only hears about quality when something goes wrong. | ✓Early visibility Leadership starts seeing trends before they become production incidents. |
×Tribal knowledge Team knowledge lives inside experienced engineers' heads. | ✓Shared knowledge Team knowledge becomes part of your everyday development workflow. |
×Review overload AI increases code output but also increases review pressure. | ✓Balanced AI output AI increases productivity without overwhelming your review process. |
Type the domain you are pointing at your server and every command and dashboard link on this page fills itself in with it. Remembered in this browser, editable any time.
Want to look around first?
Sign in to the shared demo organization to see a fully configured LiveReview with two weeks of review history behind it, then come back and run these steps on your own.
Email: [email protected]
OTP: 729651
Connecting takes minutes. By day 2, every repo, every commit, and every PR or MR across your whole team is being reviewed, plus scheduled sweeps run across the codebase. Screenshots throughout show a fully configured organization, so you can see what each step looks like done.
- Your git host, AI provider, Slack/Teams/email, and local tools: all wired in one sitting.
- Commit-level, PR or MR level, and scheduled reviews running across every repo, for the whole team.
Checklist for this phase
0 of 16 done
From day 3, responding to review comments becomes part of how your team ships. You won't review code just one way. You'll use whichever trigger fits the moment.
- Developers reply to and act on review comments right inside the PR or MR.
- Team starts exploring API/MCP access, different review levels, and custom rules.
- The system starts picking up on your team's patterns and preferences.
Checklist for this phase
0 of 6 done
From day 7, a standards doc your own team leads helped write: the rules you've been enforcing by hand, now enforced on every diff.
- Customization finalized with the people who own that code.
- One centralized view: every review, every repo, real time.
- Recurring issues start surfacing on their own.
Checklist for this phase
0 of 2 done
From day 12, a report with your organization's name on it: top contributors, change volume, issues by category.
- Every issue classified by category: security, performance, reliability, and more.
- Fewer defects reaching your customers means safer, faster, more reliable releases.
Checklist for this phase
0 of 5 done
Ready to run this on your own organization?
Everything above runs the same way on your repos, your team, and your standards, just with your own results at the end of it.