Schedule a demo

See hiring built around real engineering work

See how CodeSubmit handles take-home projects, Bytes screening tasks, live CodePair interviews, and visible AI use in one system so your team can review faster without losing judgment.

01
Real assessments, not toy prompts
See take-home projects and Bytes screens built around practical engineering work.
02
Visible AI use in context
Review prompts, responses, and candidate judgment instead of treating AI like a blind spot.
03
Faster review and cleaner follow-up
Move from repo-based submissions into live CodePair sessions without resetting the conversation.
Book your walkthrough
Tell us a bit about your team. We'll tailor the demo to your hiring stages, your roles, and the part of the workflow you want to improve first.
We usually reply within one business day.
What you’ll see

The full hiring loop, not a disconnected feature tour

We’ll walk through how teams screen, review, interview, and evaluate AI-assisted work in one workflow, with candidate experience and reviewer judgment staying central.
Assessments that match the role
Start with take-home projects or Bytes screens that feel closer to real work than whiteboard trivia.
AI in plain sight
See how candidates use AI, where reviewers speed up with summaries, and where judgment stays human.
Live follow-up in the same context
Carry shortlisted work into CodePair so interviews stay anchored to the repo instead of a fresh prompt.
Demo agenda

We tailor the walkthrough to the stages you actually run

If you need better early screens, stronger repo-based interviews, or a clearer way to evaluate AI-native development, we can focus the demo on the parts of the workflow that matter most.
01
Start with the stage you need to improve
We can focus on early screening, take-home projects, live interviews, or the full workflow depending on where your current process breaks down.
02
See candidate signal in real artifacts
Review commits, code, test output, and AI usage the same way your team would review engineering work internally.
03
Continue the conversation live
Watch how CodePair picks up from the repo, keeps prompts visible, and helps reviewers probe tradeoffs without losing context.
04
Map the rollout to your team
We’ll talk through ATS fit, reviewer workflows, challenge coverage, and where learning or AI readiness fits after hiring.
Review signal
What your team leaves with
A clearer view of how CodeSubmit fits your current process, where it saves review time, and how to introduce visible AI evaluation without making hiring feel automated.
Recommended starting point
A practical first rollout based on your team size, roles, and current hiring bottlenecks.
Reviewer workflow clarity
A clear view of how your team would review work faster without handing off the decision to automation.
AI policy fit
A concrete way to evaluate AI-assisted work without pretending candidates are not using foundation models.
Questions answered in context
We tailor the walkthrough to your stack, your roles, and the parts of the workflow that matter most.