Weave
Engineering intelligence that attributes every commit and token to a human or an AI agent, then scores what your AI coding spend returned.
Worth a real look the moment someone above you asks what the Cursor and Claude Code spend returned. AI attribution plus prompt routing is a pairing the delivery-metrics vendors don't sell, and the free Starter tier makes the evaluation cheap. Go in knowing Router carries its own quote, and that the scores are only as good as the version control and telemetry you hook up first.
Last checked 1d ago · cite: rightaichoice.com/tools/weave
- CTOs and VPs of Engineering who must justify AI coding spend to a board or CFO
- Scale-ups running Cursor, Claude Code, and Copilot side by side with no unified usage view
- Platform and DevEx teams asked to cut token spend without losing output quality
- Teams that want AI metrics, DORA, and SPACE in one reporting layer instead of three dashboards
- Teams under 5 engineers — the free Starter tier covers org metrics and is likely the whole ceiling
- Organizations without standardized version control or consistent PR conventions to score against
- Buyers who want delivery metrics bundled with developer experience surveys, which Weave doesn't sell
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Skip Weave if your team is under five engineers or your total AI coding spend is small — $50/engineer/month for Pro, billed monthly, will cost more than the subscriptions it measures, and Starter's org-level metrics are likely your whole ceiling.
Pro is priced per engineer per month at $50 billed monthly, so the bill scales linearly with headcount — a 40-engineer org is roughly $2,000/mo before any Router spend.
Starter is free and genuinely usable at org level, which puts Weave's entry point below Swarmia and Waydev-style per-seat analytics contracts. Pro at $50/engineer/month billed monthly (16.67% off yearly) sits in the same band as LinearB and Jellyfish per-seat pricing but bundles AI attribution those tools don't sell. Above roughly 100 engineers, custom Enterprise pricing and separately quoted Router costs push Weave past a simple per-seat comparison.
In short
Weave — Engineering intelligence that attributes every commit and token to a human or an AI agent, then scores what your AI coding spend returned. Best for CTOs and VPs of Engineering who must justify AI coding spend to a board or CFO, Scale-ups running Cursor, Claude Code, and Copilot side by side with no unified usage view, Platform and DevEx teams asked to cut token spend without losing output quality. Free to start; paid plans from $50/mo.
What people actually say about Weave — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
65 mentions across 3 sources (Hacker News, App Store, Lemmy) · researched Jul 3, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Several Hacker News posts align with Weave's core mission of measuring AI+human productivity.
- +The concept of normalizing AI and human contributions is timely and addresses a real need.
- +DORA metrics benchmarks and agent observability fill a gap in the market.
- +The product description promises deep integrations (GitHub, Jira, Slack, etc.).
- +Freemium pricing lowers the barrier for teams to try it.
- −No direct community feedback suggests the product is not widely used or discussed.
- −Brand confusion with other 'Weave' products makes it hard to find relevant information.
- −The broader developer community shows skepticism about productivity scoring metrics.
- −All App Store reviews are for a different product, not the engineering analytics platform.
- −No reviews on Reddit, Product Hunt, or other major tech platforms.
- • Unclear if AI-specific metrics (AI ROI, AI impact) require a premium tier
- • Potential overage costs for large teams or high data volume
- • May require existing subscriptions to GitHub/GitLab/Jira for integrations
Viability Score
How well maintained and how widely used is Weave? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Attribute commits, pull requests, reviews, deploys, and tokens to a human or an AI agent
- Output score measuring engineering output against calibrated benchmarks
- AI usage, AI impact, AI ROI, and AI health reporting alongside DORA and SPACE
- Token intelligence benchmarking token spend against 1,000+ engineering organizations
- Agent observability across 50+ AI coding tools with per-engineer AI usage and AI score
- Weave Router classifies each prompt and routes it to a model on cost, speed, and quality
- Router installs via npx -y @weave-os/router behind Anthropic, OpenAI, and Google clients
- Router CLI and HTTP decide endpoint for scripted routing
- Router learns routing policy from feedback across your team over time
- Astra routing mode marketed as quality at half the cost
- Wooly AI engineering agent answers natural-language questions in-app with cited records
- Wooly available through MCP for querying your own engineering data
- Code intelligence covering output, quality, reviews, and code turnover
- Dev FinOps ties engineering cost to business value delivered
- Real-time dashboards tracking AI usage, output, and quality trends
About Weave
Weave is engineering intelligence for teams that have to show what their AI coding spend bought. It pulls commits, pull requests, reviews, deploys, and AI telemetry into a single reporting layer, then lines AI usage up against engineering output, code quality, and cost. The vendor cites 2M+ PRs analyzed, 25k+ engineers, 50+ AI tools, and 500+ engineering organizations from startups to Fortune 100. The product reports an output score, AI usage, AI impact, AI ROI and AI health, plus code turnover and token intelligence that benchmarks token spend against 1,000+ organizations. Reporting combines AI metrics with DORA and SPACE, so you can see where work stalls from prompt to production rather than only how much AI was used. Two pieces stand apart from the delivery-metrics crowd. Wooly, the in-app engineering agent, answers plain-language questions against your own records and cites them, and is also reachable over MCP. Weave Router classifies each prompt and sends it to a model on cost, speed, and quality, installed through npx -y @weave-os/router behind Anthropic, OpenAI, and Google clients while the client keeps working unchanged. The site benchmarks DeepSeek V4, GPT-5 Codex, Claude Sonnet 5, and Claude Opus 4.8 on cost against quality, and markets an Astra mode as quality at half the cost. Pricing splits into two products. The platform is free on Starter, $50/engineer/month on Pro billed monthly with 16.67% off yearly, and custom on Enterprise. Router is quoted separately. Versus DX, Jellyfish, LinearB, Swarmia, and Waydev, the split is scope: those compare on delivery metrics and developer experience, while Weave adds AI attribution and model routing.
Behind the Verdict
The honest way to judge Weave is to ask whether AI coding tools are a line item you must defend. If they are, the free Starter tier answers a surprising amount: output score, AI ROI, code turnover, and org-level usage, process, and quality metrics, at $0 for teams under five. We'd start there rather than in a demo. Pro at $50/engineer/month billed monthly is the point where it gets personal. You get PR drill-down, individual and team stats, Wooly, AI Insights, and user permissions, and yearly billing takes 16.67% off. For a 40-engineer org that is roughly $2,000 a month before the Router conversation, so the case has to rest on decisions the data actually changes, not on dashboard completeness. Where Weave pulls ahead of Jellyfish, LinearB, Swarmia, and DX is attribution: it credits each commit, PR, and token to a human or an agent, then lines that against output and quality. The delivery-metrics tools will tell you cycle time; they won't tell you which engineer's Copilot usage is actually converting. Pair that with token intelligence benchmarked against 1,000+ organizations and you have a number you can take to a CFO. Weave Router is the more interesting bet and the harder one to budget. It classifies each prompt and routes on cost, speed, and quality behind your existing Anthropic, OpenAI, or Google client, learns from team feedback, and reports an estimated cost like 1/38th of frontier with 3ms overhead. Weave's own September 2026 argument is that routing signal lives in the agent trajectory, not the prompt, which is a fair dig at cheap turn classifiers. But Router is quoted separately, so treat it as a second purchase decision. In practice, budget wiring time. The measurements are only as good as the version control and PR conventions feeding them, and
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Real-world workflow fit
Concrete scenarios for the personas Weave actually fits — and what changes day-one when you adopt it.
Connect GitHub and the AI coding tools on day one, then check the Starter output score and AI ROI dashboards before anyone pays. Once the CFO asks for per-engineer detail, move to Pro, open PR drill-down, and use Wooly to answer 'which teams get the most output per AI dollar?' with cited records.
Outcome: An executive-ready answer tying AI coding spend to measured output, benchmarked against 1,000+ organizations, without building the reporting layer in-house.
Install Router with npx -y @weave-os/router behind the existing Anthropic, OpenAI, and Google clients, generate a router key, and let Weave classify each prompt and route it on cost, speed, and quality. Run npx @weave-os/router status to see where traffic lands, and review the cost-versus-quality ratings for DeepSeek V4, GPT-5 Codex, Claude Sonnet 5, and Claude Opus 4.8.
Outcome: Lower cost per unit of work while the developers keep using their existing clients, which are unaware of the proxy.
Use AI impact and AI health reporting plus Dev FinOps to connect token spend to business value, cross-checked against DORA and SPACE metrics in the same reporting layer. Pull the Reducto-style before/after view to show measured change since rollout.
Outcome: One board slide that shows what the AI budget returned, instead of three dashboards that disagree.
Use Cases
- Track AI tool adoption and its impact on code quality and delivery speed across teams.
- Measure normalized engineering output per developer, benchmarked against industry percentiles.
- Identify bottlenecks in code review cycles and PR processes using drill-down analytics.
- Quantify the ROI of AI coding assistants like Cursor or Claude Code with AI-specific metrics.
- Route prompts to the best model automatically to reduce token cost without losing output quality.
- Generate executive reports combining DORA metrics, cost data, and team productivity trends.
- Use the Wooly agent to ask natural language questions about engineering org activity.
- Optimize engineering spend with Dev FinOps tracking cost per feature or per sprint.
Models Under the Hood
as of 2026-10-18
Limitations
- Weave's value depends on integrating with major development tools; widescale output depends on the model and agent integrations it supports.
- The free Starter plan is limited to basic usage and teams under 5, and does not include PR drill-down, individual/team stats, or the Wooly AI Agent, which require the $50/engineer/month Pro plan (billed monthly; yearly billing takes 16.67% off).
- Enterprise-grade requirements (GitHub Enterprise support, dedicated Slack channel, custom invoicing and payment terms, custom DPA and terms of service) need custom Enterprise pricing, which can slow procurement.
- Router is a second product quoted separately from platform plans, so a Router rollout is a distinct budget conversation.
- Per-engineer AI usage and AI scores create governance questions about performance management that the tool itself does not resolve.
as of 2026-10-10
Verification history
We have re-verified Weave 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 10 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Weave tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Starter
$0
Ideal for
Teams under 5 engineers, or any org that only needs org-level AI ROI, code turnover, and usage/process/quality metrics before committing budget.
What this tier adds
Free entry point: output score, AI ROI, code turnover, and org-level AI usage, process, and quality metrics — no per-engineer detail.
Pro
$50/engineer/mo billed monthly (16.67% off yearly)
Ideal for
Small to mid-size engineering teams that need to see AI impact per engineer and per team, and want to query the data with Wooly.
What this tier adds
Adds PR drill-down, individual engineer stats, team stats, the Wooly AI Agent, AI Insights, and user permissions for $50/engineer/mo billed monthly.
Enterprise
Custom
Ideal for
Larger teams optimizing an established AI coding program, and any org whose procurement requires a custom DPA and invoicing terms.
What this tier adds
Adds GitHub Enterprise, a dedicated Slack support channel, custom invoicing and payment terms, a custom DPA, and custom pricing.
Where the pricing makes sense
The company stage and team size where Weave's pricing actually pencils out — and where peers do it cheaper.
Starter is free and genuinely usable at org level, which puts Weave's entry point below Swarmia and Waydev-style per-seat analytics contracts. Pro at $50/engineer/month billed monthly (16.67% off yearly) sits in the same band as LinearB and Jellyfish per-seat pricing but bundles AI attribution those tools don't sell. Above roughly 100 engineers, custom Enterprise pricing and separately quoted Router costs push Weave past a simple per-seat comparison.
Setup time & first value
How long it actually takes to get something useful out of Weave — broken out by persona, not the marketing-page minute.
Expect the same day for Starter: connect version control and AI tool telemetry, then the org-level output score and AI ROI dashboards populate. Pro adds PR drill-down, per-engineer and team stats, Wooly, and AI insights once permissions are set. Router is a single command — npx -y @weave-os/router — that detects your clients and writes one env var per provider. Reducto reported 14 days from
Switching to or from Weave
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From spreadsheet-based AI cost tracking: connect GitHub and your AI coding tools to Weave, then replace manual token tallies with the token intelligence benchmarks against 1,000+ organizations.
- →From Jellyfish or LinearB: keep your existing DORA and delivery reporting, add Weave alongside for AI attribution and per-engineer AI usage, and compare the two output views before consolidating.
- ↗To DX or Swarmia: if you decide you need delivery metrics plus developer-experience surveys rather than AI attribution, those vendors bundle the survey layer Weave doesn't sell.
- ↗To a direct model-provider billing console: if your AI spend is low enough that $50/engineer/month exceeds the subscriptions being measured, drop the analytics layer and track spend in the provider dashboards.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Weave”, and we withheld 6: 6 could not be judged, because “Weave” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Weave.
Official links
Tools that pair well with Weave
Common stack mates teams adopt alongside Weave, with the specific reason each pairing earns its keep.
Bito
Bito Governor is an AI model router with a code context engine that cuts coding-agent spend by 40-70%.
MLflow
Open source AI engineering platform for agent and LLM tracing, evaluation, prompt management, and ML lifecycle work.
Codacy AI
Codacy AI Reviewer enforces AI guardrails and pulls request code review for agentic coding teams
Featured Head-to-Head Comparisons
Weave vs Spider Cloud
Spider Cloud and Weave serve entirely different needs: Spider Cloud is a web data extraction API for feeding AI models, while Weave is an engineering analytics platform to measure AI coding productivity. Choose Spider Cloud if you need real-time web data for RAG or AI agents; choose Weave if you're an engineering leader tracking AI-assisted development impact. They are not direct competitors.
Weave vs Screenplayiq
ScreenplayIQ is purpose-built for screenwriters and producers needing data-driven box office forecasts, while Weave targets engineering leaders measuring AI-assisted development. They serve completely different domains, so the choice depends entirely on your role: script analysis vs. engineering productivity. Neither tool overlaps, so pick the one that matches your industry.
Weave vs Temporal Ai
Temporal AI and Weave serve fundamentally different needs: Temporal is for building resilient, fault-tolerant workflows and AI agents that survive failures, while Weave is an analytics platform to measure engineering productivity and AI ROI. Choose Temporal if you need to orchestrate durable, long-running processes; choose Weave if you need to quantify the impact of AI coding tools across your engineering organization. They are complementary — you could use both together.
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