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Hivel VS Linear B

LinearB vs Hivel: which one fits your team?

LinearB is built for teams that want faster PR flow today. Hivel is built for the question that comes after: is our AI coding spend shipping real outcomes, and what should we fix next.
Free AI ROI Report

Get the full picture on your AI adoption and impact.

We'll show you exactly how AI is impacting your speed and code quality.

NO CODE ACCESS
FREE AI ROI REPORT
NO CREDIT CARD
4.7/5
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Read-only access · no engineering lift · runs alongside LinearB, Jira, and your existing CI/CD.
1000+
Engineering Teams
4.7/5
on G2
48 hrs
to first insight
TL;DR
LinearB is built for pipeline speed

It gives you standard delivery dashboards, showing your numbers, but without tracing AI code lineage or telling you what to fix next.

Hivel answers a different question

Which AI-generated code shipped safely, which caused rework or an incident, and what to fix next, connected across your whole lifecycle, not just the PR.

Compare the pricing and plans

LinearB’s full tier costs $59 / user/month, while Hivel’s Growth plan delivers the same complete lifecycle features for $20 per contributor per month billed annually (or $25 monthly).

Free AI ROI Report

Get the full picture on your AI adoption and impact.

We'll show you exactly how AI is impacting your speed and code quality.

NO CODE ACCESS
FREE AI ROI REPORT
NO CREDIT CARD
4.7/5
See Full Pricing
The 10-second verdict

Two different jobs, Scale vs. Coach

Workflow automation for the pipeline you have today

LinearB reads your Git and Jira data, shows DORA and cycle-time metrics on a dashboard, and automates PR routing and nudges through gitStream and WorkerB. Built for engineering managers who want the pipeline moving faster right now.

AI-outcome intelligence across the whole lifecycle

Hivel connects Git, CI/CD, Jira, and incident data into one graph. It detects which code was AI-generated down to the commit, traces what happened to that code in production, and recommends the next action. Developers, managers, and executives all work from the same picture - alongside the delivery visibility you already expect.
Same question, different answer

What each tool tells you when you ask it something real

The figures below are representative examples of the kind of answer each tool returns, not results from a named customer.

How productive is my team right now?

LinearB says
142 PRs shipped this sprint. Cycle time 3.2 days. Review time down 18%.
Hivel says
142 PRs, but 38 were rework on last sprint's work, and 22 of those were fixes to AI-generated code. Net new delivery is down 15% month over month, concentrated in one team.

What's the impact of our AI coding tools?

LinearB says
Not measured - LinearB tracks PR and pipeline metadata, not code provenance.
Hivel says
73% Copilot adoption, but AI-authored code carries 2.1x more rework and is linked to 5 of the last 8 production incidents. One team's AI code actually outperforms its human code; the difference is test coverage.

Why did last night's incident happen?

LinearB says
Deployment frequency and lead-time metrics for the affected service, on the DORA dashboard.
Hivel says
Traced to a specific PR merged six hours earlier, tied to a ticket whose requirements explicitly ruled out the change that caused it, in a module with an identical incident three months ago.
side by side

LinearB Vs Hivel

Dimension LinearB Hivel
Built to do Automate and measure the software delivery pipeline: PR flow, cycle time, DORA metrics. Connect intent, code, delivery, and production into one graph.
Data model Per‑tool metadata: Git and Jira events read individually, shown on dashboards. A live, cross‑tool context graph spanning requirement, ticket, commit, PR, deploy, and incident, so any metric can be traced back to the work behind it.
Time to first dashboard Fast, low‑friction setup. Read‑only connection in hours, first usable insight within 48 hours for most teams; the full lifecycle graph and ranked recommendations land within days.
AI code detection at commit level Not available: metadata‑only, cannot distinguish AI‑written from human‑written lines. Proprietary AI Code Telemetry model, traced through PR, deployment, and production.
AI spend to shipped outcome Not offered. SURGE, Hivel's AI spend module: connects tool spend and licence utilisation to shipped features and recoverable waste.
Who acts on the data Primarily engineering managers, on a dashboard. Developers, managers, and executives, on the same underlying graph, surfaced where they already work.
Deployment Cloud‑hosted SaaS. Cloud, on‑prem, or multi‑cloud available.
DORA metrics, Jira and GitHub integration Table stakes — both platforms offer this.
Price From $29/mo (GitHub Cloud only); Full platform access requires the $59/user/mo plan + credit limits. Growth: $20/contributor/mo billed annually ($25 monthly)for 20–200 devs, with full multi-tool/multi-stack support included. Enterprise custom above 200.
Proof, not adjectives

Results Hivel customers report

After adopting Hivel, Freshworks reported a reduction in hotfix rate and an increase in feature throughput.
26%
FEWER HOTFIXES
+16%
more features shipped
6-8x

typical ROI within 6 months (Hivel data)

1,000+

engineering teams on Hivel

19%

cycle-time improvement,
Sopra (Euronext: SOPR)

56%

faster release cycles, AvidXchange (NASDAQ: AVDX)

LinearB

Rated #8 Easiest to Use and in the top 10 for software development analytics.

4.6/5
Read LinearB reviews on G2 →
Hivel

Rated #1 Easiest to Use and #3 Highest Rated in software development analytics.

4.7/5
Read Hivel reviews on G2 →
Pricing, both sides

What each one actually costs

$59
/ user / month, full tier
- $59/user/mo + 1,500 credit limit.
- $29/mo (GitHub Cloud only, credit-restricted).
- Billed per user account + credit consumption.
$25
/ user / month, billed annually
- Growth plan annual billing saves 20%.($20/mo per user)
- Billed per code committer only (PMs, QA, and EMs free).
- Deployment available Cloud, On-Prem, and Multi-Cloud supported for all.
- Custom flat pricing for 200+ developers.

Know your AI leverage in 48 Hours

Hivel connects your whole lifecycle, from requirement to production incident, into one graph, detects AI-generated code at the commit level, and recommends the next action. LinearB tells you the number; Hivel tells you what to do about it.

What LinearB gets right?
LinearB's gitStream automation can auto-label PRs, route reviewers by risk, and nudge stuck work through WorkerB. If your main complaint is "our PRs sit too long," that is exactly the problem LinearB solves, and it solves it with very little setup.
Which one is right for you

Two different questions, two different tools

Stay with LinearB if…

Your immediate goal is faster PR review and cleaner cycle-time reporting, not AI-spend accountability.
You want gitStream policy and WorkerB automation running in the pipeline today, with minimal setup.
You are not yet running AI coding tools at scale, so there is no AI-lineage question to answer.

Add or switch to Hivel if…

Your question has moved from "are we shipping faster" to "is our AI coding spend making us better, or just faster at creating problems."
You need to trace a specific commit through PR, deployment, and production incident - and know whether it was AI-generated.
You run more than one AI coding tool or more than one Git host, and need one graph instead of per-tool dashboards.
Who Hivel is not for?
If your team is small, not yet running AI coding tools at meaningful scale, and your only open question is "how do we get PRs reviewed faster," Hivel is more than you need right now. LinearB's gitStream and WorkerB automation will solve that problem directly, with less setup, and its free tier covers teams of up to 10 contributors. Come back to Hivel when the question changes from speed to outcomes.

Frequently asked questions

What's the difference between LinearB and Hivel?

LinearB measures delivery velocity on static dashboards, relying on automated reviewer alerts to clear PR bottlenecks. Hivel goes beyond flat metrics: it detects AI code at the commit level, traces downstream production risks, and pushes contextual recommendations to developers and leadership where they already work.

Is Hivel a LinearB alternative?

For teams whose main need has shifted from pipeline speed to AI-spend accountability, yes. For teams that mainly want faster PR review today, LinearB remains the better direct fit - see "Who Hivel is not for" above. Many teams run both.

How much does Hivel cost compared to LinearB?

Hivel is $25 per contributor per month ( $20 billed annually for 20–200 devs), billing only active code committers while PMs, QA, and leadership access the platform for free with zero credit caps.LinearB starts at $29 per month (Essentials, GitHub Cloud only) on a credits-based system, scaling up to $59 per user per month plus credit limits on Enterprise.

Can Hivel tell which code was written by AI?

Yes, at the commit level, using Hivel's proprietary AI Code Telemetry model, and Hivel then traces that code through PR, deployment, and production to show what happened to it. LinearB does not offer this; it works from Git and Jira metadata, not code content.

How long does it take to set up Hivel?

Connection is read-only and typically takes hours, with a first usable insight inside 48 hours for most teams. The full context graph and ranked recommendations usually land within a few days, faster for a single-repo team and slower for a large multi-tool estate.

Still deciding?

Run both. Hivel connects read-only in an afternoon, and you can compare answers on your own data before committing to anything.
Free AI ROI Report

Get the full picture on your AI adoption and impact.

We'll show you exactly how AI is impacting your speed and code quality.

NO CODE ACCESS
FREE AI ROI REPORT
NO CREDIT CARD
4.7/5