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Specs unlocking AI agents
for your Engineering Team
Specs unlocking AI agents
for your Engineering Team
Specs unlocking AI agents
for your Engineering Team
Ship software faster with AI-ready specs by streamlining
handoffs between your human teams and AI agents
Ship software faster with AI-ready specs by streamlining handoffs between your human teams and AI agents
The Solution
The Solution
The Solution
Specs are the new interface for software development
Lyra turns messy, multiplayer context into
one-shot, AI-executable specs, fine-tuned for coding, design, and QA AI agents
Lyra turns messy, multiplayer context into one-shot, AI-executable specs, fine-tuned for coding, design, and QA AI agents
Start with an intent
Start with an intent
Link your PRD or start a project from scratch
Collaborate with Lyra to get Specs
Lyra asks clarifying questions to flag ambiguities and edge cases to generate AI-ready specs
Engage AI agents to ship faster
Lyra generates one-shot prompts for AI coding, design and QA agents
The Problem
The Problem
The Problem
Missing context &
scattered team decisions
are a deal‑breaker
for AI agents
AI agents hallucinate when specs are vague or lack edge-case coverage, leading to rework
Critical project context is burries across tools like Slack, docs, and meetings
30%
of engineering time is lost due to
AI-gen code rework
52%
companies face security
risks, due to AI-gen code
Benefits & Use Cases
Benefits & Use Cases
Benefits & Use Cases
From startups running background coding agents to teams shipping into large codebases,
Lyra makes AI execution reliable
From startups running background coding agents to teams shipping into large codebases, Lyra makes AI execution reliable
From startups running background coding agents to teams shipping into large codebases, Lyra makes AI execution reliable
🎯 Cross-Team Alignment
Structured specs for every role, so PMs, engineers, designers, QAs and AI agents
🎯 Cross-Team Alignment
Structured specs for every role, so PMs, engineers, designers, QAs and AI agents
🎯 Cross-Team Alignment
Structured specs for every role, so PMs, engineers, designers, QAs and AI agents
⚡ Multi-Agent Orchestration
Coordinate multiple coding, design, and QA agents in parallel
⚡ Multi-Agent Orchestration
Coordinate multiple coding, design, and QA agents in parallel
⚡ Multi-Agent Orchestration
Coordinate multiple coding, design, and QA agents in parallel with specs
🔍 Edge-Case Safety Net
Expose edge cases and hidden assumptions—reduce rework and costly misalignment
🔍 Edge-Case Safety Net
Expose edge cases and hidden assumptions—reduce rework and costly misalignment
🔍 Find Edge-Cases
Clarify hidden assumptions before implementation—avoid back-and-forth
🔗 Context from Day 1
Auto-ingest product, code, and business context from day one: Slack, Notion, GitHub, and more
🔗 Context from Day 1
Auto-ingest product, code, and business context from: Slack, Notion, GitHub, and more
🔗 Context from Day 1
Auto-ingest product, code, and business context from day one: Slack, Notion, GitHub…
🔁 Propagation Across Tools
Decisions sync everywhere—Lyra keeps Slack, GitHub, and Notion in sync with the live spec
🔁 Propagation Across Tools
Decisions sync everywhere, Lyra keeps Slack, GitHub, and Notion in sync with the live spec
🔁 Propagation Across Tools
Decisions sync everywhere—Lyra keeps Slack, GitHub, and Notion in sync with the live spec
🧠 Graph Knowledge Memory
Every spec improves the next—Lyra builds a persistent memory of your team’s decisions and patterns
🧠 Graph Knowledge
Every spec improves the next. Lyra builds a persistent memory of decisions and patterns
🧠 Graph Knowledge Memory
Every spec improves the next—Lyra builds a persistent memory of your team’s decisions and patterns
🧩 Agent-Ready Specs
Lyra transforms tickets into one-shot prompts tailored for tools like Cursor, Devin, or v0, etc
🧩 Agent-Ready Specs
Lyra transforms tickets into one-shot prompts tailored for tools like Cursor, Devin, or v0, etc
🔧 Plug-and-Play Setup
No lengthy onboarding or change management—Lyra fits right into your team’s existing stack
🔧 Plug-and-Play Setup
No lengthy onboarding or change management. Lyra fits right into your existing stack
🔧 Plug-and-Play Setup
No lengthy onboarding or change management—Lyra fits right into your team’s existing stack
🔐 Data Security & Privacy
Your data is private. Your context stays yours.
Lyra does not train LLMs on your data,
your context is used solely for your workflowsWe’re actively working toward SOC 2 Type I compliance as part of our security roadmap
🔐 Security & Privacy
Your data is private. Your context stays yours.
Lyra does not train LLMs on your data, your context is used solely for your workflows
We’re actively working toward SOC 2 Type I compliance as part of our security roadmap
Save money
$50k
$50k
Save up to $50k per eng annually on rework from project ambiguity
Faster
2x
Teams build and ship faster with AI-ready, ambiguity-free specs
Save time
30%
Save up to 30% of your engineers' time related to AI-gen code rework
Easily integrate your tools
Easily integrate your tools
Easily integrate your tools
Bring Lyra into your workflow
Lyra connects to the tools your team already uses
Pull in context, decisions, and existing specs with zero disruption
What teams say about Lyra
What teams say about Lyra
What teams say about Lyra
Trusted by engineers, PMs, designers, and QAs to ship faster, by integrating AI agents without the overhead
Anton Skliar
CTO at AIR Media-Tech
CTO at AIR Media-Tech
Using Lyra has significantly streamlined our project management process. The initial task generation was impressive, especially for frontend tasks...
What’s the pricing?
Using Lyra has significantly streamlined our project management process. The initial task generation was impressive, especially for frontend tasks...
What’s the pricing?
Using Lyra has significantly streamlined our project management process. The initial task generation was impressive, especially for frontend tasks...
What’s the pricing?
Ready to build faster with AI-ready specs?
From fast-moving startups to global enterprises—teams use Lyra to spec faster, align better, and unlock real AI execution across eng, product, design, and QA.
Wow! Lyra will save us a lot of time because this would be the first exact question from our engineering team during our backlog discussion meeting and Lyra discovered this edge case!
Wow! Lyra will save us a lot of time because this would be the first exact question from our engineering team during our backlog discussion meeting and Lyra discovered this edge case!
Tim Alexandrov
CPO at INFLU2
CPO at INFLU2
FAQ
FAQ
FAQ
What is Lyra?
Lyra helps engineering orgs fix the product-to-engineering handoff. It pulls scattered project context from PRDs, ERDs, Slack threads, and meeting notes, resolves ambiguities, flags edge cases, and aligns constraints across stakeholders. The result: clear, up-to-date specs and tasks synced with Jira or Linear that both engineers and AI coding agents can execute without costly revision cycles
Who uses Lyra?
Product and engineering teams at startups, scale-ups, and enterprises adopting AI coding agents like Cursor, Devin, Claude to accelerate complex feature delivery
How does Lyra reduce rework?
By spotting vague requirements and missing edge cases early, Lyra prevents downstream clarifications and syncs, cutting up to 25–40% of wasted engineering time
How is Lyra different from AI coding assistants?
AI coding assistants execute code. Lyra ensures the instructions they receive are complete, precise, and aligned across the team — unlocking their full potential.
Does Lyra work for multi-repo or complex projects?
Yes — Lyra handles large codebases, multiple repositories, and cross-team dependencies by keeping all specs synchronized with the latest decisions.
What is Lyra?
Lyra helps engineering orgs fix the product-to-engineering handoff. It pulls scattered project context from PRDs, ERDs, Slack threads, and meeting notes, resolves ambiguities, flags edge cases, and aligns constraints across stakeholders. The result: clear, up-to-date specs and tasks synced with Jira or Linear that both engineers and AI coding agents can execute without costly revision cycles
Who uses Lyra?
Product and engineering teams at startups, scale-ups, and enterprises adopting AI coding agents like Cursor, Devin, Claude to accelerate complex feature delivery
How does Lyra reduce rework?
By spotting vague requirements and missing edge cases early, Lyra prevents downstream clarifications and syncs, cutting up to 25–40% of wasted engineering time
How is Lyra different from AI coding assistants?
AI coding assistants execute code. Lyra ensures the instructions they receive are complete, precise, and aligned across the team — unlocking their full potential.
Does Lyra work for multi-repo or complex projects?
Yes — Lyra handles large codebases, multiple repositories, and cross-team dependencies by keeping all specs synchronized with the latest decisions.
What is Lyra?
Lyra helps engineering orgs fix the product-to-engineering handoff. It pulls scattered project context from PRDs, ERDs, Slack threads, and meeting notes, resolves ambiguities, flags edge cases, and aligns constraints across stakeholders. The result: clear, up-to-date specs and tasks synced with Jira or Linear that both engineers and AI coding agents can execute without costly revision cycles
Who uses Lyra?
Product and engineering teams at startups, scale-ups, and enterprises adopting AI coding agents like Cursor, Devin, Claude to accelerate complex feature delivery
How does Lyra reduce rework?
By spotting vague requirements and missing edge cases early, Lyra prevents downstream clarifications and syncs, cutting up to 25–40% of wasted engineering time
How is Lyra different from AI coding assistants?
AI coding assistants execute code. Lyra ensures the instructions they receive are complete, precise, and aligned across the team — unlocking their full potential.
Does Lyra work for multi-repo or complex projects?
Yes — Lyra handles large codebases, multiple repositories, and cross-team dependencies by keeping all specs synchronized with the latest decisions.