Lyra Chrome Extension vs Weave: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Lyra Chrome Extension and Weave — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Lyra Chrome Extension
Lyra
Run AI-native meetings by moving your call onto Lyra for AI-assisted research, live collaboration, and automated follow-ups.
Key features
- Pre-Meeting AI Research: Runs automated AI-driven research and context gathering before meetings to surface relevant information and prepare participants.
- AI-Native Meeting Hosting: Allows users to move their call onto Lyra so the meeting operates with built-in AI assistance rather than treating AI as an external tool.
- Live Follow-Up & Draft Creation: Generates follow-ups, draft messages, and documents during the meeting, enabling immediate capture and refinement of next steps.
- Real-Time Task Extraction: Identifies action items and converts them into assignable tasks live in the meeting to reduce manual note-taking.
- Screenshare-Free Collaboration: Enables collaborative drafting and information sharing within the meeting environment, minimizing the need to screenshare.
- Browser Integration: Installs as a Chrome extension to embed Lyra's meeting and AI features directly into users' browsing and meeting workflows.
- AI-native meeting environment: move calls onto Lyra to run meetings with integrated AI assistance
- Pre-meeting research assistance to prepare for calls
- Live generation of follow-ups, drafts, and tasks during meetings
- Chrome extension distribution via Chrome Web Store
- Real-time team collaboration features (no screenshare required)
Best for
- Pre-Meeting Preparation: Automatically gather and summarize background research and key topics for participants to review before the call.
- Live Meeting Assistance: Use the extension during a call to generate talking points, synthesize discussion, and produce polished drafts in real time.
- Instant Action Item Management: Detect and convert decisions and requests from the meeting into tasks assigned to team members without leaving the call.
- Collaborative Drafting: Co-author emails, proposals, or follow-up documents with teammates during the meeting without screensharing.
- Meeting Summaries: Produce concise post-meeting summaries and next-step lists immediately after the call to speed up execution.
- Preparing for meetings with automated research and briefing materials
- Running live meetings with AI-generated notes, follow-ups, and action items
- Collaborative drafting of documents or messages during calls
- Replacing screenshare workflows with shared AI-assisted meeting space
Weave
WorkWeave
Engineering intelligence platform that measures the ROI of AI coding spend and routes every prompt to the most cost-efficient model.
Key features
- 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.
- Wooly Engineering Agent: An AI agent that reviews all your engineering data to suggest where and how to improve, answering questions grounded in your own records with citations, available in-app or over MCP.
- Standard Framework Reporting: DORA and SPACE metrics plus survey data combined with AI-specific measures in one pane of glass for executive reporting.
- Enterprise Compliance Controls: SOC 2 Type II certification with regular third-party audits, GDPR and HIPAA compliance, SSO via SAML and OIDC, SCIM provisioning, and role-based access.
Best for
- 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.
- Ad-Hoc Engineering Questions: Asking Wooly where deployment cycles are getting stuck and receiving an answer cited back to the organisation's own records.