Weave
AI engineering intelligence: measure developer output and AI ROI from prompt to production
If you spend seriously on AI coding tools and can't answer what you're getting for it, Weave is the most direct answer on the market. Its AI attribution and Prompt Router are genuinely differentiated, though the per-engineer price and setup mean it pays off most for teams already deep in AI-assisted workflows. For lighter needs, DX or LinearB may suffice, but for AI ROI, Weave leads.
Verified 4d ago · liveness 74/100 · cite: rightaichoice.com/tools/weave
- Engineering leaders at scale-ups and enterprises adopting AI-assisted development
- CTOs and VPs of Engineering needing to quantify AI ROI and productivity
- Teams using multiple AI coding tools (Cursor, Claude Code, Copilot) who need unified observability
- Organizations transitioning to AI-augmented workflows who need to measure impact
- Small teams (under 5 engineers) that do not use AI coding tools
- Organizations without a standardized version control system (e.g., GitHub, GitLab)
- Teams looking for free, unlimited analytics without any paid tier
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Skip Weave if you're a small team under 5 engineers not using AI coding tools, or if you lack GitHub/GitLab integration—most features will be useless.
Pro tier is $50/engineer/month, so a 50-engineer team costs $2,500/month annually, adding up quickly.
Weave's freemium Starter works for small teams, but Pro at $50/engineer/month is aimed at scale-ups and enterprises already spending on AI. Compared to DX or LinearB, Weave is pricier but adds AI ROI and router features that can offset costs. Annual billing saves 16.67%.
In short
Weave — AI engineering intelligence: measure developer output and AI ROI from prompt to production. Best for Engineering leaders at scale-ups and enterprises adopting AI-assisted development, CTOs and VPs of Engineering needing to quantify AI ROI and productivity, Teams using multiple AI coding tools (Cursor, Claude Code, Copilot) who need unified observability. Free to start; paid plans from $50/mo.
What's new in Weave
Checked yesterdayAcross the latest 8 updates: 1 feature update and 7 news mentions.
79% of the time, the model you asked for isn't the model you needed
Weave finds 79% of model requests in production don't match the model needed.
Agent traffic is 62% cache reads, and it should change how you think about routing
62% of agent traffic is cache reads — routing should be adjusted accordingly.
From 8 requests to 12,000 a week: how a new frontier model takes over a fleet
New frontier model can scale from 8 to 12,000 weekly requests, taking over a fleet.
Detecting doom loops: what 582 spirals in production taught us about coding agents
582 production doom loops reveal patterns in coding agent failures.
The top 10 models our router actually uses, and what each one is for
Weave publishes its router's top 10 models and their intended uses.
Your agents are paying frontier prices to read tool output
Agents overpay for tool output reads; suggests routing and caching improvements.
Weave Raises $13.5M Series A to Build Engineering and Token Intelligence
Weave raises $13.5M Series A for engineering and token intelligence.
AI Engineering Analytics Platform: Unlock Faster Developer Output
New AI engineering analytics platform aimed at faster developer output.
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.
- +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: September 2026
How we score →Key Features
- Attribution of contributions to humans vs AI agents
- Output score calibrated to expert benchmarks
- AI health, AI impact, AI ROI metrics
- Agent observability for Cursor, Claude Code, GitHub Copilot
- Prompt Router auto-routes to cost-efficient models (DeepSeek V4, GPT-5 Codex, Claude Sonnet 5)
- Token intelligence with benchmarking across 1000+ orgs
- Wooly AI agent answers natural-language questions (in-app and via MCP)
- DORA metrics: deployment frequency, lead time, MTTR, change failure rate
- Real-time team tracking dashboards
- Code intelligence: output, quality, reviews, turnover
- Dev FinOps: engineering cost-to-value analysis
- SSO (SAML & OIDC) and SCIM provisioning
- SOC 2 Type II, GDPR, HIPAA compliance
- Integrations with 50+ AI tools
- Prompt Router CLI and SDK (npx @workweave/router, API)
About Weave
Weave is an engineering intelligence platform that shows engineering leaders the ROI of every AI dollar spent, from prompt to production. It ingests data from version control, code reviews, CI/CD, and project management to deliver a unified view of the software development lifecycle. Using LLMs and ML, Weave attributes every contribution—whether from humans or AI agents—to the right engineer, normalizing work into an output score benchmarked against expert standards. This makes it possible to see exactly how AI coding assistants like Cursor, Claude Code, and GitHub Copilot affect team speed and quality. Beyond standard DORA and SPACE metrics, Weave adds AI-specific metrics: AI health, AI impact, and AI ROI. You also get agent observability to see how your team actually uses AI tools, token intelligence to track where token spend goes and benchmark it across 1000+ organizations, and a Dev FinOps view that ties engineering cost to business value. A standout feature is the Weave Prompt Router, which automatically routes each prompt to the most cost-efficient model—such as DeepSeek V4, GPT-5 Codex, or Claude Sonnet 5—without sacrificing speed or quality, learning from your feedback over time. You can invoke it via a simple CLI or API. Another differentiator is Wooly, an AI engineering agent that answers natural-language questions about your org (like "Which engineers use AI most effectively?") with answers grounded in your own data, available in-app or via MCP. Weave is SOC 2 Type II certified, GDPR and HIPAA compliant, and supports SSO (SAML & OIDC) and SCIM provisioning. Trusted by 500+ organizations from startups to Fortune 100, it's built for engineering leaders who need to prove AI value and optimize engineering spend. The free Starter tier works for small teams; Pro at $50/engineer/month unlocks individual stats and the Wooly agent—pricing that suits scale-ups and enterprises needing to quantify AI's impact. Compared to DX, LinearB, and Swarmia, Weave's unique
Behind the Verdict
Weave targets a specific pain: engineering leaders who've poured money into AI coding assistants and can't quantify the return. The platform's AI attribution—splitting contributions between humans and agents, then scoring output against expert benchmarks—is its sharpest edge. It turns vague AI hype into a per-engineer number, which is exactly what a CTO needs when defending budget. The Prompt Router is a clever cost play. It classifies every prompt and sends it to the cheapest model that can handle it—DeepSeek V4 for routine edits, Claude Opus 4.8 for tough ones—cutting token spend dramatically. The CLI and API make it drop-in for teams already using Anthropic, OpenAI, or Google models. The recent Series A funding suggests Weave is doubling down on this direction. But Weave isn't for everyone. Pricing starts at $50 per engineer per month, which adds up fast for larger teams. The Starter tier is free but capped at team-level data—you won't see individual stats or the Wooly agent without Pro. If you're a small team not yet using AI tools, you'll get little value and pay a premium. Also, the setup requires standardized version control and project management; teams with messy tooling will struggle to get clean data. Compared to DX or LinearB, Weave is more AI-centric. DX focuses on developer experience and productivity, LinearB on delivery metrics. Weave goes further with AI-specific metrics like AI ROI and agent observability, plus the router. For teams just starting to measure DORA, those rivals might be simpler. But for AI-heavy orgs, Weave's scope is hard to beat. One caveat: the value depends on your team's adoption of AI coding tools. If only a few engineers use Cursor or Copilot, the per-engineer cost won't justify the insights. But if your whole org is
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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.
After integrating GitHub and Cursor, CTO wants to see which engineers benefit most from AI and where bottlenecks are.
Outcome: Within a few days, Weave provides individual AI usage scores and output benchmarks, revealing that senior engineers gain 31% output, and identifies PR review bottlenecks to address.
Tasked with justifying $200k annual spend on AI coding tools to the board.
Outcome: Weave's AI ROI dashboard shows a 44% AI-assisted merge rate and quantifies cost savings via token intelligence, presenting a compelling ROI case.
Wants to reduce token spend across multiple AI tools without sacrificing quality.
Outcome: Sets up Weave Router, which routes prompts to cost-efficient models like DeepSeek V4, cutting costs by up to 1/38th while maintaining quality scores, and uses Wooly to ask 'Where are our deployment cycles getting stuck?'
Use Cases
- Track AI tool adoption and its impact on code quality and delivery speed across teams.
- Measure normalized engineering output per developer, benchmarking against industry percentiles.
- Identify bottlenecks in code review cycles and PR processes using drill-down analytics.
- Quantify ROI of AI coding assistants like Cursor or Claude Code with AI-specific metrics.
- Route prompts to the best model automatically to reduce costs and improve output quality.
- Generate executive reports combining DORA metrics, cost data, and team productivity trends.
- Use Wooly AI agent to ask natural language questions about engineering org activity.
- Optimize engineering spend with Dev FinOps tracking cost per feature or sprint.
Models Under the Hood
as of 2026-08-28
Limitations
- Weave's value depends on integrating with major development tools; without GitHub/GitLab data, many features are unavailable.
- The free Starter plan is limited to basic metrics and does not include PR drill-down or the Wooly AI Agent.
- The $50/engineer/month Pro price can get expensive for larger teams, and enterprise-grade security (like GitHub Enterprise support and custom DPA) requires a custom Enterprise contract, which may slow procurement.
as of 2026-08-24
Verification history
We have re-verified Weave 7 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 7 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 wanting basic org-level metrics and AI ROI tracking at no cost.
What this tier adds
Free entry point with output score, AI ROI, code turnover, and org-level AI usage, but no individual stats or Wooly.
Pro
$50/engineer/mo
Ideal for
Small to mid-sized teams needing per-engineer stats and AI agent insights to scale AI adoption.
What this tier adds
Adds PR drill-down, individual and team stats, Wooly AI Agent, and AI Insights, at $50/engineer/month.
Enterprise
Custom
Ideal for
Large organizations with security, compliance, and custom procurement needs.
What this tier adds
Custom pricing adds security & compliance features, GitHub Enterprise support, dedicated Slack channel, custom DPA and invoicing.
Where the pricing makes sense
The company stage and team size where Weave's pricing actually pencils out — and where peers do it cheaper.
Weave's freemium Starter works for small teams, but Pro at $50/engineer/month is aimed at scale-ups and enterprises already spending on AI. Compared to DX or LinearB, Weave is pricier but adds AI ROI and router features that can offset costs. Annual billing saves 16.67%.
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.
Most teams are live within a day: install the CLI or connect GitHub/GitLab via OAuth, and data starts flowing. Executive reports are generated within 14 days as per customer story.
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 Spreadsheets: Connect GitHub/GitLab and export historical data to populate Weave's dashboards.
- →From DX or LinearB: Export your metrics and import into Weave; Weave's API can ingest historical data.
- →From in-house scripts: Use Weave's CLI/API to push data and replace custom analytics.
- ↗To DX: Export Weave data via API and map to DX's metrics.
- ↗To LinearB: Bring your historical DORA metrics and replicate in LinearB's dashboards.
- ↗To a custom analytics stack: Use Weave's API to pull data into your own BI tools.
Integrations
Resources & Guides
Tutorials & Learning
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
AI model router and code context engine that cuts agent token spend by grounding requests in your codebase and routing to right-sized
MLflow
Open source platform to debug, evaluate, monitor, and optimize AI agents and ML models.
Maxim AI
Simulate, evaluate, and observe AI agents—ship reliable agents 5x faster with Maxim.
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.
Alternatives to Weave
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