14,328 pain signals detected today

Find people already talking about the problem you solve.

Paste your website. Inreach maps the operational pain your future customers are publicly describing, and shows you the moments to act, weeks before they search for a vendor.

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Or try:
Monitoring across
X / Twitter LinkedIn· Reddit (soon)· HN (soon)
See how it works

Real posts in. Scored signals and reply drafts out.

Actual Linkedin, X, Reddit and Hacker News posts, surfaced in your feed with match context and a reply draft.

The thesis

The market is talking.
Most teams aren't catching pain early.

01
Operators publicly describe what's broken, every hour.
Founders vent on X. RevOps leads crowdsource solutions on LinkedIn. CFOs disclose dispute volumes. This is the most honest market research on earth, and it's all public.
02
Most GTM teams never see it.
Saved searches return noise. Social listening tools track brand mentions. Intent platforms wait until someone visits a vendor page. By then the buying window is already closing.
03
Pain shows up before purchase intent.
The pattern is consistent: a metric breaks, an operator complains, a vendor search begins. Inreach catches the first signal, usually 2 to 8 weeks before traditional intent platforms register anything.
04
Inreach detects those moments in real time.
Eleven category-specific pain models run on every public post within seconds of publication. Signals are scored, contextualized, and routed to your feed based on what your product solves.
05
You reach out while urgency is still happening.
Read the signal. Understand the context. Reach out before the budget conversation. The window is small, typically two to four weeks. Inreach exists so you don't miss it.
Pain volume · this week1,481 total
Attribution chaos
412+38%
CRM bloat / migration
267+12%
Support volume
198+24%
Outbound channel decay
156+19%
Tool fatigue
142+27%
Stripe / payment ops
121−4%
Fractional CMO ask
98+44%
Refreshed 23s ago · sample = 14,328 public posts
Real public posts

This is what live
buying intent looks like.

Actual posts from real operators, not templates, not examples. Each one is operational pain in the window before vendor evaluation begins. Click any card to read the original.

Harsh Garg
@HarshGarg06
Apr 2026
Burned through 2 support hires in 6 months. After analyzing 3 months of tickets: 61% were FAQ questions, same answer every time. Both hires were answering $40K/year questions that consumed 5+ hours of their 8-hour day.
Support scaling · deflectionView original ↗
Soyoon Lee
@sylearners
Jan 2025
Spent $5,000 on Meta ads across AI products. Cost per actual user: $150–200. Conversion rate: 1.8–2.4%. Clicks were $3.50–$4.80 each. The leads had zero intent, just people clicking ads.
Paid acquisition · Meta CACView original ↗
thereisnotry
Founder, Prepfully
Nov 2023
I got a bunch of fraudulent chargebacks, and lost disputes even where people acknowledged they made the chargeback by accident. I submitted the email thread. The bank sided against me anyway.
Payment fraud · chargebacksView original ↗
UvrajSB
Co-founder, Zingle
2025
Shipped a PR that triggered repeated full refreshes on a large model and it turned into a $50k Snowflake bill. Senior data engineers had no time for thorough reviews while AI-assisted code volume kept accelerating.
Data cost · warehouse spendView original ↗

Real public posts · linked to original sources · Inreach detects thousands like these every day

Used by

Real teams are
already monitoring.

“Inreach generated 300% more highly qualified leads in a single weekend and increased engagement on X by more than 20%.”
DataAgentsDataAgents·growth ops · since Q1
“We had to pause the campaign because Inreach was driving too many buyers into our beta.”
WhisprWhispr·founder-led GTM
The gap

Why most GTM teams
miss live demand.

The existing stack wasn't built for this. Social listening was built for brand monitoring. Sales intelligence was built for cold lists. Intent data was built for late-funnel scoring. None of them watch for pain, the earliest, highest-signal layer of the buying process.

The old stack
Keyword tools, saved searches, intent platforms, all looking in the wrong place.
  • ×Keyword alerts return brand mentions, not the pain that precedes intent.
  • ×Saved searches scale to 5 queries on a Monday morning, not 50 categories.
  • ×Social listening tools track share-of-voice, not operational reality.
  • ×Intent platforms wait until someone visits a vendor page, weeks too late.
  • ×By the time it's in your CRM, the buying window is already closing.
Pain intelligence
A real-time intelligence layer built specifically for operational pain.
  • Eleven pain-category detection models running on every public post in real time.
  • Matched against your product context, not a brand string or domain match.
  • Scored by urgency, specificity, and stated timeline, not reach or sentiment.
  • Each signal surfaces the conversation, the context, and who should engage.
  • Live operational demand visible in the window where you can actually act.
How it works

From a public post
to a signal in your feed, in under 90 seconds.

Four stages, end to end. Nothing batched, nothing scheduled. The feed goes live the moment your workspace exists.

STAGE 01
Continuous ingestion
Inreach maintains a live read of public X and LinkedIn conversations. Reddit + HN in beta. Post-to-pipeline latency averages 11 seconds.
x · stream14.3k/min
STAGE 02
Pain pattern detection
Eleven category-specific models trained on the actual language operators use, attribution, CRM, support, hiring, payments, tooling, outbound, costs, churn.
STAGE 03
Context + product fit
Each signal is matched against your product context, what you solve, who feels it, which verticals buy. Generic noise gets dropped before it ever hits your feed.
northline.app93% match
STAGE 04
Surface the moment
Live feed with the full context, the post, the pain pattern, the buying window, the suggested angle. Read-only by default. You decide whether and how to act.
97
91
89
Worked examples

The pain shape is different
in every vertical.

Inreach keeps a category map per vertical, the patterns operators use, the metrics they reference, the language they fall into when something breaks. Pick one to see what we'd surface for you this week.

The pain
Activation drop-offs, onboarding friction, magic-link breakage, PLG metrics flatlining.
The signal we detect
Founders venting about session replay needs, activation drops, mobile onboarding holes, usually in /buildinpublic threads.
The opportunity
Asking for product analytics, session replay, or onboarding-builder recommendations within 24 hours of the complaint.
Confidence

Audit every signal.
No black-box claims.

Every signal carries provenance, the original post, the matched pattern, the confidence score, the latency. You can see why each decision was made the same way you'd audit a production system.

Post → feed · median
73ms
From the moment a post is published to the moment it lands in your feed, scored and contextualized.
Pain detection precision
91%
Audited against an internal benchmark of 18,000 operator-labelled signals across 11 categories.
Public posts processed
14.3k/hr
Continuous ingest from X and LinkedIn. No batching, no scheduling, no four-hour sync windows.
After the signal

What you do with a signal
is up to your team.

Inreach is observability first. Workflows are intentionally light, routing, digests, saved views, optional drafts. The platform never sends anything on your behalf. That decision belongs to a human.

Routing rules
Route signals by pain type, vertical, or intent stage. Attribution signals to growth, CRM bloat to RevOps, support pain to CS. Each route gets its own threshold and destination.
EVENT-DRIVEN · CONDITIONAL
Digests + alerts
Daily Slack digest of the top signals matching your filters. Email summaries for execs. Real-time alerts above your confidence floor. You set the noise threshold.
SLACK · EMAIL · WEBHOOK
Saved views
Pin any pattern, 'DTC CACs climbing,' 'CRM migrations in healthcare.' Views update live as new signals match. Export to CSV or push to your CRM.
FILTER · TAG · EXPORT
Optional reply drafts
If you want a starting point for a contextual reply, Inreach drafts one. It's yours to edit, send manually, or discard. Nothing goes out automatically. No bulk reply flows.
DRAFT · HUMAN APPROVE
Integrations

Monitors where buyers vent.
Pushes where your team works.

Detect operational pain across the public conversations operators are already having, and route the high-signal moments straight into the tools your team already uses.

Monitors here
Where operators actually vent.
Public-only ingestion across the four surfaces where operational pain shows up in plain English.
X / TwitterLIVE·primary source
LinkedInLIVE·primary source
RedditBETA·select subreddits
Hacker NewsBETA·front + new
Public posts only · no DMs, no scraped emails
Pushes here
Where your team already collaborates.
Route qualified signals into the surfaces your team checks every day, without adding another dashboard to live in.
SlackDigests · live alerts
NotionSaved views · export
HubSpotPush qualified signals
More destinations on request
Pricing

Persistent agents
continuously uncovering market pain.

Each plan is a number of agents quietly running in the background, watching for the operational pain your future customers are publicly describing. Start with one, grow into a full intelligence layer.

Watch
For founders exploring market demand.
$0free forever
Agents1active
Refresh cadenceOnce daily
SourcesX
  • Opportunity feed with full context
  • Daily digest to Slack or email
  • Save and tag opportunities
  • Single user
Scout
For founders and operators actively exploring their market.
$39/ month · billed yearly
Agents3active
Refresh cadenceEvery 6 hours
SourcesX + LinkedIn
  • Saved opportunity views + tagging
  • Daily Slack digest
  • Export to Notion
  • 30-day opportunity history
  • Solo operator workflow
Intelligence
For companies operationalizing market intelligence.
$399/ month · billed yearly
Agents20+active
Refresh cadenceHourly · priority
SourcesX · LinkedIn · Reddit · HN
  • Advanced routing rules + filters
  • Historical opportunity archive
  • API access
  • Multi-workspace support
  • Priority processing
  • Up to 15 seats
Enterprise
A dedicated intelligence layer for your category.
Bespoke deployments for revenue, product, and research teams who need their own infrastructure, sources, and agent footprint.
  • Managed engagement, done for you
  • Dedicated processing infrastructure
  • Custom agent limits + refresh cadence
  • Custom integrations + private sources
  • White-glove onboarding + setup
  • Direct line to our team
CUSTOM PRICING · 30-MIN INTRO
· 14-day trial on Operator + Intelligence· No outreach automation, ever· Cancel any time
FAQ

Questions operators
actually ask.

Is this social listening?+

No. Social listening tools surface keyword mentions and brand sentiment. Inreach detects operational pain, the moment someone describes a workflow that broke, a tool they've outgrown, or a metric heading the wrong way. Pain shows up weeks before any vendor search.

How is this different from outbound automation tools?+

Outbound tools send messages to lists. Inreach is the opposite, it tells you which conversations are already happening, why they matter, and when the buying window opens. Inreach never sends anything on your behalf.

What signals does it detect?+

Eleven categories today: attribution chaos, CRM bloat, tool switching, hiring pain, support overload, revenue leakage, workflow breakage, vendor evaluation, churn signals, paid-channel decay, and explicit buying intent. Each has its own detection model.

Where does the data come from?+

Public conversations on X and LinkedIn. Reddit and Hacker News are in beta. Only public posts, no DMs, no scraped emails, no off-platform data.

How real-time is it?+

Median signal-to-feed latency is under 90 seconds for X and under 5 minutes for LinkedIn. Detection runs on every relevant post as it's published, not on a batch schedule.

Does Inreach reply or message anyone?+

No. Read-only by default. You can optionally draft a contextual reply inside Inreach and approve-then-post manually. We never send anything without explicit per-message approval. No bulk reply workflows exist.

How accurate is the detection?+

On our internal benchmark, 18,000 operator-labelled signals across 11 categories, precision is 91% and recall is 84%. Every signal shows the matched pain pattern and a confidence score, so you can audit it.

What does this replace?+

TweetDeck/saved searches, manual social monitoring spreadsheets, Slack channels piped from keyword alerts, and the 'check what people are saying' hour every Monday morning.

The takeaway

People are publicly describing the exact problem your product solves. Right now, you're missing those conversations.

Drop your URL. In under five minutes, Inreach maps the operational pain your future customers are publicly talking about, and turns your workspace into a live demand intelligence feed.

Start watching Talk to sales
· Free to start watching· No outreach automation· Live in 5 minutes