Weave
AIEngineering intelligence platform that measures the ROI of AI coding spend and routes every prompt to the most cost-efficient model.
Weave
Engineering intelligence platform that measures the ROI of AI coding spend and routes every prompt to the most cost-efficient model.
About Weave
Weave is an engineering-intelligence platform that combines LLMs and machine learning to analyse every action from prompt to production — commits, tokens, pull requests, reviews, deploys, and AI telemetry — and scores cost, efficiency, and quality rather than raw consumption. It merges novel AI-impact metrics with established DORA and SPACE frameworks and survey data into a single view that shows where a team is getting stuck, with per-engineer breakdowns of AI usage, AI score, code quality, and output against a baseline. Its token intelligence layer benchmarks return on token spend across more than 1,000 organisations, and the Weave Router classifies each prompt and sends it to the model with the best quality-per-token, installed with a single npx command that detects existing clients and writes one env var per provider so the client is unaware of the proxy. Wooly, its AI engineering agent, answers questions grounded in the organisation's own records with citations, and is callable in-app or through MCP. Weave reports SOC 2 Type II certification, GDPR and HIPAA compliance, SSO via SAML and OIDC, and SCIM provisioning.
Screenshots
Key Features
Use Cases
Frequently asked questions about Weave
What is Weave?
Engineering intelligence platform that measures the ROI of AI coding spend and routes every prompt to the most cost-efficient model.
How does Weave work?
Weave works by combining Prompt-to-Production Analysis: LLM and ML models analyse commits, tokens, pull requests, reviews, deploys, and AI telemetry as a single pipeline rather than isolated metrics., AI ROI Scoring: Token consumption is scored for cost, efficiency, and quality, benchmarked against thousands of engineering organisations, so spend is measured by value rather than volume., Per-Engineer AI Impact: A breakdown of AI usage rate, AI score, code quality, and output change versus baseline for each engineer over a rolling window., Weave Prompt Router: Classifies every prompt and routes it to the most cost-efficient model without compromising speed or quality, learning from individual and organisation-level feedback., One-Command Router Install: Running npx @workweave/router detects your existing clients and writes one env var per provider for Anthropic, OpenAI, and Google, with the bearer token staying on your device unless you export it. to help users with Justifying AI Tooling Spend: Producing an executive report on what a Claude Code or Cursor rollout actually returned, benchmarked against peer organisations., Cutting Inference Costs: Routing routine edits to cheaper models and reserving frontier models for work that needs them, without changing how developers work., Finding SDLC Bottlenecks: Identifying where pull requests, reviews, or deploys stall using DORA and SPACE metrics alongside AI telemetry., Coaching Engineers on AI Use: Seeing which engineers get real quality and output gains from AI assistance and which are consuming tokens without effect., Agent Observability: Tracking what autonomous coding agents contribute to the codebase separately from human-authored work..
What are the main features of Weave?
Key features include Prompt-to-Production Analysis: LLM and ML models analyse commits, tokens, pull requests, reviews, deploys, and AI telemetry as a single pipeline rather than isolated metrics., AI ROI Scoring: Token consumption is scored for cost, efficiency, and quality, benchmarked against thousands of engineering organisations, so spend is measured by value rather than volume., Per-Engineer AI Impact: A breakdown of AI usage rate, AI score, code quality, and output change versus baseline for each engineer over a rolling window., Weave Prompt Router: Classifies every prompt and routes it to the most cost-efficient model without compromising speed or quality, learning from individual and organisation-level feedback., One-Command Router Install: Running npx @workweave/router detects your existing clients and writes one env var per provider for Anthropic, OpenAI, and Google, with the bearer token staying on your device unless you export it..
Who is Weave for?
Weave is useful for anyone interested in Justifying AI Tooling Spend: Producing an executive report on what a Claude Code or Cursor rollout actually returned, benchmarked against peer organisations., Cutting Inference Costs: Routing routine edits to cheaper models and reserving frontier models for work that needs them, without changing how developers work., Finding SDLC Bottlenecks: Identifying where pull requests, reviews, or deploys stall using DORA and SPACE metrics alongside AI telemetry., Coaching Engineers on AI Use: Seeing which engineers get real quality and output gains from AI assistance and which are consuming tokens without effect., Agent Observability: Tracking what autonomous coding agents contribute to the codebase separately from human-authored work..
How much does Weave cost?
Weave offers a free tier with paid plans for advanced features.
How do I get started with Weave?
Visit https://weaveos.com/ to sign up and explore Weave.
Explore more AI Ai Tools tools
Browse all Ai Tools tools →Compare Weave: vs Mise · vs BiBimba · vs VoiceCap · vs NM Signals