Feedback is everywhere. Insight is nowhere.
Customer signal lives across Intercom, Gong, Slack, support tickets, and sales notes. Manually synthesizing it is so labor-intensive that most of it is simply lost.
Agentic user research at scale, right in Claude.
Build better products for your customers, by processing 100% of scattered customer signals.
- Scale Product automations
- Find actionable signals
- Save billions of tokens
- Get better answers faster
- Verify & drill down easily
- Spread best practices
SOC 2 Type II
GDPR Ready
OAuth 2.1
Zero data retention by clients
USER INTERVIEW
SALES CALL
TEAM THREAD
LIVE CHAT
SUPPORT TICKET
FEATURE REQUEST
Product ContextNEEDS0PAIN POINTS0KEY QUOTES0FEEDBACK0
PRODUCT KNOWLEDGE GRAPH
Meet Evermuse
A 90-second intro from Eran Dror,
Cofounder & CEO.
Book a Demo with the Founders
11.8×Faster Time
to Market
to Market
17.2Hours/Month Saved
Per Team Member
Per Team Member
How it works
From every customer signal to better product decisions.
Evermuse sits between your sources and your agent, continuously transforming scattered information into structured product understanding.
01
Process 100% of customer signals.
Continuously process calls, feedback, support conversations, CRM activity, and other customer evidence - not just the items someone happens to ask about.
02
Continuously build product understanding.
Organize needs, pain points, personas, requests, capabilities, segments, and product decisions into a structured model that keeps evolving.
03
Generate evidence-backed AI specs.
Give your agent the customer context, product constraints, and strategic rationale it needs to turn ideas into grounded specs.
04
Keep development aligned.
Carry product intent from discovery into implementation, reviews, revisions, and the next decision - without losing the why along the way.
Grounded beats generic
Why this beats “just ask Claude”
A generic AI doesn't proactively learn from what your customers said in last Tuesday's call. Evermuse does.
With Evermuse
Claude + Evermuse
- Billion Token SavingsSave billions of tokens on ingestion, processing, and recall.
- Better, Faster AnswersGet better answers faster with pre-processed context.
- Citation Clips & Drill DownsDrill down on any claim to verified sources and relevant clips.
- 100% Complete PictureSee the full pattern, not a set of anecdotes.
- Objective DecisionsGround every decision, PRD, or discussion in real customer data.
- Methodology UpliftSpread best practices & methodology to EVERY internal user.
- Trusted AutomationsTrust Claude to do more complex and nuanced Product and dev tasks with timely, relevant, and dynamic context.
Without Evermuse
Claude Alone
- −Waste Tokens Every RunSpend tokens badly processing sources every time from scratch.
- −Wait Longer for Worse AnswersWhy get fast grounded answers when you can get slow bad answers.
- −No Drill-Down or VerificationYou have to trust Claude implicitly because the sources are not easy to verify.
- −Anecdotal EvidenceThere is nothing that Claude loves better than writing convincing reports based on anecdotal evidence of a few sources.
- −Subjective Vibes That “Feel” Like ResearchFeels good to trust Claude and not think too hard about the thoroughness of its research.
- −Battle of the PromptsGreat prompters get great answers, bad prompters get equally convincing & eloquent bad answers.
- −Fragile AutomationsAutomate only extra clear tasks because nuanced ones require deep context.
The problem
AI made engineering faster. That made Product's job harder.
Your team can ship in hours now. But nobody has time to figure out what to ship. Customer signal is scattered, discovery is rushed, and specs are thin - if they exist at all.
No time to do the work that matters.
AI coding means everything ships faster than ever. For Product, that means no time for discovery, no time to write proper PRDs, no time for research.
Pressure from every direction.
Engineering wants specs yesterday. Leadership wants roadmap confidence. Customers want to feel heard. You're caught in the middle.
The bottleneck has shifted.
Cursor, Codex, and Claude Code can write features in minutes - but they can't decide which feature to write. The constraint is no longer engineering capacity. It's product clarity.
The context-layer choice
Vibe coding is for CRUD,
not a mature AI stack.
A prototype can run on prompts and scripts. Company-wide intelligence needs a durable, governed layer built to keep working.
Managed & compounding
Evermuse Context Layer
- Process 100% of SignalsNothing ever needs to get lost in a centralized managed source-of-truth.
- From Signal to ActionConnect customer evidence to company goals, roadmap decisions, specs, and next steps - not another report that gathers dust.
- Reliable by DesignRun every source through a maintained, repeatable pipeline with structured evidence and citations you can verify.
- Built for the Whole CompanyGive product, sales, finance, and leadership one governed workspace - no terminal, GitHub, or expert prompting required.
- Maintained for YouKeep ingestion, workflows, and integrations improving without assigning someone internally to own the entire system.
Local & owner-dependent
Home Grown Context Layer
- −Limited by Context Window, Local TokensAn agent can do very little processing of sources in a single run.
- −Insights in a Siloed ReportClaude can collect and organize signals, but tying them to strategic goals and driving the next action still falls on your team.
- −A Fragile Homegrown PipelineCustom skills and scripts work until edge cases, redaction mistakes, or the last few hallucinations quietly compound.
- −Works for the Builder, Not the TeamA local Claude setup can be powerful for its creator while leaving everyone else without a shared, governed way to use it.
- −Another System You Have to SupportPrompts, skills, scripts, and connectors need a dedicated owner. When that person gets busy, the pipeline stops evolving.
From the team
Watch the latest webinars.
72 minON DEMAND
September 2026The Role of Product in the Age of AI
Greg Biggers (VP Product & Design, Airship) and Eran Dror on where AI actually moved the product bottleneck: from writing code to validating the right problem, from PRDs to product briefs, and from waiting for permission to just building.
Eran Dror
98 watched
80 minON DEMAND
August 2026From Gut Feel to Real Signal
David Sternberg (author of The Flow Equation) and Eran Dror on why UX is shifting from gut-feel art to measurable science, adaptive interfaces, and where nudging turns into manipulation.
Eran Dror
131 watched
75 minON DEMAND
July 2026Giving Claude Product Superpowers
A practical playbook for wiring Claude into the tools your work runs on: customer sources, analytics, ticketing, scheduled tasks, and agentic memory, via MCPs, skills, and plugins.
Eran Dror
207 watched
Stay inside the tools you already use
Claude knows code & language. Evermuse helps it know your product & customers.
Evermuse is not another UI your team has to learn. It makes the agent they already use product-aware.
Claude + Evermuse“Give me a spec for the onboarding changes enterprise accounting firms are asking for.”
Best-in-class UIs
Best-in-class UIs for those who want them.
When chat is not the best interface.
SUGGESTIONS
Identify & ship Product opportunities 12X faster with AI Suggestions.
- Prioritize by ROI, customer requests, and sales blockers.
- Identify both explicit requests and implicit opportunities.
- Stay connected to the original quotes and sources.
- Get the clarity you need, in the time you have.
1 / 6
Not another memory layer
Generic memory gives AI agents access to past history. Evermuse builds product understanding.
Generic memory
- Retrieves documents.
- Waits for questions.
- Is one-size-fits-all.
- Returns context.
Evermuse
PRODUCTSCAPABILITIESCUSTOMERSCOMPETITORSNEEDSREQUESTSTRANSCRIPTSSIGNALSOPPORTUNITIESPAYMENTS
- Builds product understanding.
- Continuously processes every signal.
- Is purpose-built for product teams.
- Connects evidence to decisions.
Your demo
Book a Demo with the Founders
No slides. No canned walkthrough. We analyze your real customer feedback and generate a live spec - in 30 minutes with the founding team.
30 min Your stack No commitment
11.8×Faster Time to Market
17.2Hours/Month Saved
What you'll get in 30 minutes
01
Your AI Coder, connected
See specs flow into Cursor or Claude Code via MCP - with real evidence attached.
02
Your customer feedback, analyzed
We plug into your sources or analyze a sample of customer calls you provide.
03
A PRD, generated live
Watch Evermuse turn messy feature requests into a structured, evidence-backed spec.
04
Your questions, honestly answered
Pricing, security, integrations, timeline. We answer everything directly.
What Users Are Saying
Shira Dassa
Product @ Yotpo
$436M RAISED • 600+ EMPLOYEES
"I'm reviewing the insights your product provided - my mind is blown! This is such a game-changer."
Erik Peterson
Head of Product @ ReSim.ai
SILICON VALLEY VENTURE BACKED
"[The results are] stunningly great, in my opinion... Now I don't have to attend every client interview in person."
Min Zhou
Design Lead @ OpenSea
$427M RAISED • 700+ EMPLOYEES
"Last month alone, we'd save 8.5 hours per team member using Evermuse."
Hadar Kaminski
Senior UX Researcher @ Redis
$357M RAISED • 1,000+ EMPLOYEES
"It looks like, yes - you may have cracked this complexity."
Rachel Abramowitz
Founder & CEO @ Keepler
"This is super awesome. Solves a bunch of the problems I know I have, but also ones that I'm like, I didn't know I had that problem."
Sarah Hillel
UX Researcher @ Pitango
"I love the system... A very big pain point this can fix right away... is having to explain to PMs how I got there."
Frequently asked
Evermuse
Don't let another product insight get missed.
Turn customer signals, market data, product knowledge, and strategic decisions into continuous product clarity.