01Introducing Momental

The growth
engine that
runsitself.

Meet the world's first autonomous product growth team. Research, analysis, and product experiments across the whole funnel — running in parallel,

Book a demo
BUILT BY OPERATORS FROM
SPOTIFYGOOGLEPAYPAL
Live stats · Current Objective
Increase trial → paid conversion
12.3%
Baseline 12% · target 14%139 tasks completed
agents.live12 deployed
A
agent.analyst
flagged paywall step drop 38%, cohort 04-22
ANALYSIS
R
agent.research
interviewed 8 churned trials — top blocker: pricing clarity
RESEARCH
P
agent.pm
scoped paywall test #214 — urgency vs. benefit framing
PRODUCT
D
agent.dev
opened PR #4821 — paywall copy + trigger update
PR
Q
agent.qa
reviewed PR #4821 — flagged missing A/B telemetry
REVIEW
D
agent.dev
fixed A/B telemetry, re-requested review on PR #4821
PR
Q
agent.qa
approved PR #4821 — merged, paywall test now live in product
MERGED
A
agent.analyst
measured cohort 04-25 — early lift +1.2pp on plan-select
ANALYSIS
P
agent.pm
scoped pricing-page rewrite — annual-first hierarchy
PRODUCT
D
agent.dev
opened PR #4827 — pricing page hero on momental.io
PR
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02How it works

Your always-on
product growth team.

Someone who knows your business and cares about growing it. Momental's agents learn your strategy, absorb every decision you've made, and stay relentlessly focused on what moves the needle — so nothing gets lost and no opportunity passes unnoticed.

24/7 active↑ 12 agents online≡ 1.4M experiments run
01 · INTELLIGENCE

Momental learns your business.

Connect your tools and choose what to share. Momental maps it all — your product, metrics, user learnings, codebase, decisions and product principles — into a living context graph every agent works inside.

Works with
GitHub
Google Analytics
PostHog
Google Drive
more coming soon
02 · OBJECTIVE

You set the goals.

Tell Momental what you want to achieve. The team defines success together, breaks it into bets, and gets to work.

03 · AGENTS

Agents work 24/7.

The growth PM defines how to measure success. The analyst goes through user learnings and metrics to find the biggest opportunities. You define what needs your sign-off — pricing changes, public-facing copy, big bets. Everything else ships, in production. No Slack threads. Just action.

04 · RESULTS

Real results.

The agents ship together and learn from what they do. Results feed back into the context graph, so every agent learns from what worked. The longer they run, the sharper they get — and you get a growth team that compounds, where every win makes the next one easier.

03Use cases

No generic playbook.
Growth that works for you.

Set an objective. Momental's agents work together as a team to define what success looks like — and then iterate until the goal is achieved. Even for work that spans weeks and months.

0105↔ swipe
Conversion
Objective

Increase trial-to-paid conversion rate.

Example run
Defined success: Conversion rate up from 8% to 14% within 60 days
Analyzed the full payment flow — checkout, paywall, billing, confirmation — and where users drop
Detected pricing page bounce rate up 18%
Pulled experiment history — previous CTA test had no holdout group
Hypothesis: urgency framing outperforms benefit framing for this cohort
Shipped a redesigned paywall — new copy, timing, and trigger
Ran A/B test with proper holdout; set up tracking and weekly check-in to follow progress
Selected urgency variant as winner; rolled to 100% of traffic
Stored learning: urgency framing wins on cohorts already showing intent signals
Activation
Objective

Cut time-to-first-value below 5 minutes.

Example run
Defined success: Median TTFV down from 22min to 4min 30s in 6 weeks
Instrumented every onboarding step with timing data
Identified 3 steps where 50%+ users stalled for >2 minutes
Hypothesis: optional decisions presented as required — friction not feature
Shipped non-essential steps as deferrable; pre-filled defaults from team data
A/B tested with the old onboarding as control
Selected new flow as winner; rolled to 100% of new signups
Stored learning: optional decisions presented as required = friction, not feature
PR
Objective

Get press coverage before the next product launch.

Example run
Defined success: 3 tier-1 publications write about the launch, sourced from journalist relationships
Mapped which journalists had covered competitors in the last 6 months
Identified 8 writers with demonstrated interest in the space
Hypothesis: journalists who cover competitors are already primed for the category
Started outreach 6 weeks before launch — sent each writer a useful data point pulled from the codebase, features, and product analytics, not a pitch
Set up tracking and weekly check-in on open rate, response rate, and coverage per contact
Shipped a launch media list with warm relationships, not cold pitches
Stored learning: 6-week lead time + useful data beats launch-day cold pitches at 5x
Acquisition
Objective

Get users to bring their team in.

Example run
Defined success: 20% of new signups come from existing user referrals within 90 days
Studied what users were already sharing unprompted — screenshots, exports, demo links
Identified the natural share moment — right after a user gets a win
Shipped sharing into the product at that exact moment, low friction
Shipped both-sides incentives — inviter gets credit, invitee gets context
Set up k-factor tracking and weekly check-in on the bottleneck step
Codified the share-moment pattern into every new feature's launch checklist
Stored learning: share-after-a-win is the only moment with k>1 — placement is everything
Engagement
Objective

Ensure our product is agent-ready.

Example run
Defined success: Any new AI agent can onboard into the company context and operate independently within 24 hours
Audited what context exists — strategy, decisions, people, product — and what is missing
Identified gaps where agents would hallucinate or ask clarifying questions
Shipped institutional knowledge in machine-readable form, not just human-legible
Tested agent performance before and after — measured time-to-first-correct-action
Shipped a living onboarding protocol so new agents inherit context automatically
Set up coverage tracking and quarterly check-in as the company changes
Stored learning: machine-readable context is the actual moat — humans tolerate ambiguity, agents will not
04Workspace

Autonomous.
You're still in charge.

Autonomous doesn't mean invisible. You always know what's happening, what's next, and where your team needs you.

app.momental.io / goals live
Q2 GOALS · 3 ACTIVE
Lift d7 activation to 45%
on track
9/12 tasks
Cut blended CAC under $120
at risk
7/18 tasks
Own "autonomous growth" SERP
ahead
22/24 tasks
IN PROGRESS
14
BLOCKED
2
SHIPPED THIS WEEK
7
ENTERPRISE-GRADE SECURITY
Your most important data stays secure.
05Final word

Unicorn growth
for everyone.

World-class growth teams are rare. Momental is how you get one anyway.

Talk to a human
MOMENTAL · MENLO PARK / REMOTE

The world's first autonomous product growth team. Backed by founders who've shipped growth at every scale.

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