Weave vs Span: which engineering intelligence platform is right for your team?
Weave and Span are the two most AI-native platforms in engineering intelligence, and both measure AI at the code level. The difference is what they optimize for. Span instruments the AI workflow with traces, evals, and scorecards. Weave turns all of it into one calibrated measure of output. Here's the full breakdown.
The short version
Weave measures human and AI contributions directly from code and normalizes everything into a single output unit calibrated to expert benchmarks. Span instruments the AI workflow with agent traces, effectiveness scorecards, and spend reports across many dashboards.
Teams typically choose Weave when they want one benchmarked measure of engineering output and AI ROI, with transparent pricing, a free tier, and same-day self-serve setup. Teams typically choose Span when deep agent-trace diagnostics and AI enablement coaching are the priority, and custom sales-led pricing works for them.
At a glance
How Weave and Span compare
Compare
Weave
Span (span.app)
Core approach
LLMs + ML read the code and normalize it into one output unit
Agent traces, metrics, and surveys unified into dashboards
AI vs. human attribution
Code-level attribution rolled up into benchmarked per-tool ROI
Line-level attribution tied to PRs and agent traces
Measurement unit
One normalized unit of work, calibrated to expert benchmarks
Many signals: SDLC metrics, effectiveness scores, spend reports
Primary question answered
How much real output did we get, and was AI worth it?
How are engineers using AI, and how can they use it better?
Time to value
Live before the end of the day; self-serve signup
Demo-led onboarding through sales
Pricing
Transparent: free Starter, $50/engineer Pro, custom Enterprise
Custom quotes per code contributor, via sales
AI agent for insights
Wooly: ask anything about your engineering org
Src: Q&A and reports in Slack, Claude, and ChatGPT
Finance reporting
Dev FinOps built on measured output
DevFinOps: capitalization and R&D tax credits
Compliance
SOC 2 Type II, GDPR, HIPAA, SSO/OIDC, SCIM
SOC 2 Type II, GDPR, SSO/SCIM, zero-retention AI
Scale
500+ organizations incl. Fortune 100; 2M+ PRs analyzed; 20,000+ engineers
Customers incl. Ramp, Vanta, Writer, and Carvana
What is Weave?
Weave is the engineering intelligence platform for the AI era. It uses LLMs and domain-specific machine learning to understand engineering work at the source: the code itself. Everything rolls up into a single unit of output, calibrated to expert benchmarks, so you can compare teams, tools, and time periods on one number. Weave attributes every contribution to humans or AI, measures quality and review load, and includes agent observability, Dev FinOps, and the Wooly AI agent. It's trusted by 500+ organizations, from seed-stage startups to Fortune 100 companies, with 2M+ PRs analyzed.
What is Span?
Span (span.app) is an AI-native engineering intelligence platform built around agent traces: it connects AI-assisted work to shipped code, scores AI effectiveness with evals and sentiment signals, tracks AI spend by team and tool, and coaches engineers on prompting and workflows. It also covers SDLC metrics, allocation, DevFinOps, and DevEx surveys, with the Src agent answering questions in Slack, Claude, and ChatGPT. Span is a credible, fast-moving product used by teams like Ramp, Vanta, and Writer. The difference is emphasis: Span optimizes for understanding and improving how engineers work with AI. Weave optimizes for measuring what that work produced.
The key difference
Measuring outcomes vs. instrumenting the workflow
Span's approach
Span instruments the AI workflow. Agent traces, prompt quality scores, effectiveness evals, and spend reports give you rich diagnostics on how engineers use AI and where the workflow can improve. That's valuable for enablement. But it produces many signals across many dashboards, and none of them is a single measure of output an executive can steer by.
Weave's approach
Weave measures the outcome. LLMs and domain-specific ML, tuned to your codebase, evaluate the actual engineering work, attribute it to humans or AI, and normalize everything into one benchmarked unit of output. Diagnostics matter, but decisions get made on outcomes: how much was produced, at what quality, and whether AI paid for itself.
Both platforms take AI measurement seriously. The practical question is what you need on the first dashboard your CEO sees: a workflow health report, or a single calibrated number for engineering output and AI ROI. Weave was built for the second.
Why Weave
Why teams choose Weave over Span
One number you can steer by
Span gives you many signals: scorecards, traces, spend, and sentiment. Weave rolls everything into one normalized output unit, calibrated to expert benchmarks, so leadership conversations start from a shared number instead of a wall of dashboards.
Benchmarks, not just baselines
Trends against your own history tell you if you improved. Weave benchmarks output against comparable teams, median, top 10%, and top 1%, so you know where you actually stand, not just which direction you're moving.
Transparent pricing, real free tier
Weave publishes its pricing: a free Starter plan, Pro at $50/engineer per month, and custom Enterprise plans, with self-serve signup. Span prices per code contributor through custom quotes, and you won't know the number until you've talked to sales.
Live before the end of the day
Weave is self-serve: connect your tools and see data the same day. Reducto went from install to first executive report in 60 days and measured a 19% increase in output. Span onboarding runs through a sales demo.
Proven at enterprise scale
Weave runs in 500+ organizations including Fortune 100 companies, with 2M+ PRs analyzed and 20,000+ engineers on the platform, and its output unit has been calibrated against that corpus.
Enterprise-grade, HIPAA included
SOC 2 Type II certified, GDPR and HIPAA compliant, SSO/OIDC, SCIM provisioning, and regular third-party audits. If you're in a regulated industry that needs HIPAA, Weave covers it.
When Span might be the better fit
We'd rather you pick the right tool than just pick us. If your primary goal is running an AI enablement program, coaching engineers on prompting, grading agent sessions with evals, and tuning your environment for agent performance, Span's trace-level diagnostics go deeper on that workflow than anyone. But diagnostics alone shouldn't decide it: Weave includes agent observability too, and pairs it with the thing diagnostics can't give you, a single benchmarked measure of output and AI ROI you can defend in front of a board.
Customer Story
"Our goal is to ship the highest quality product as fast as possible for our customers. We use Weave to get an objective measurement and keep ourselves honest about how we're doing."
Raunak Chowdhuri
Founder & CTO, Reducto
+19%
Increase in measured engineering output
60 days
From install to first executive report
Frequently asked questions
What's the main difference between Weave and Span?
Both are AI-native engineering intelligence platforms that measure AI at the code level. Weave normalizes all engineering work into a single output unit calibrated to expert benchmarks, so you get one number for output and AI ROI. Span instruments the AI workflow with agent traces, effectiveness scorecards, and spend reports, producing rich diagnostics across many dashboards. Weave measures outcomes; Span diagnoses the workflow.
Both Weave and Span claim AI code attribution. What's different?
The attribution itself is comparable: both identify AI-written code at a granular level. The difference is what happens next. Span ties attribution back to agent traces for workflow investigation. Weave converts attribution into a normalized, benchmarked output unit, so you can compare the ROI of Cursor vs. Claude Code vs. human work on one scale, across teams and quarters.
How much do Weave and Span cost?
Weave publishes transparent pricing: a free Starter plan, Pro at $50 per engineer per month, and custom Enterprise pricing. Span does not publish prices. It charges per code contributor through custom quotes arranged with its sales team.
How long does it take to get started with Weave vs Span?
Weave is self-serve: teams connect their tools and are live before the end of the day, no sales call required. Span onboarding starts with a demo and custom pricing conversation.
Does Weave have agent observability like Span's agent traces?
Yes. Weave includes purpose-built observability for autonomous coding agents, measuring their output the same way it measures human work. Span goes deeper on trace-level workflow diagnostics like prompt quality and session investigation; Weave goes deeper on turning agent work into benchmarked output and ROI.
Is Weave enterprise-ready?
Yes. Weave is SOC 2 Type II certified, GDPR and HIPAA compliant, and supports SSO (OIDC) and SCIM provisioning, with regular third-party audits. It's used by Fortune 100 companies and supports GitHub Enterprise.
Can I switch from Span to Weave?
Yes. Weave connects directly to your existing tools, including GitHub and your project management stack, and calibrates automatically to your codebase. Most teams see their first data the same day. Book a demo and we'll map your current Span reporting to Weave equivalents.
Diagnostics tell you how AI was used. Weave tells you what it was worth.
One calibrated measure of engineering output and AI ROI. Transparent pricing, a real free tier, live before the end of the day.
The engineering intelligence platform for the AI era.
Trusted by engineering teams from seed stage to Fortune 500