← PRODUCT
On Demand Intelligence Reports
Turn a company or person’s name into a prospect-ready research file.
Account & Person Intelligence turns a company name into ICP fit with the reasons, what’s changing inside the company, who’s on the buying committee, and what each of them actually cares about. It runs in the background.
One run answers the whole account: whether to work it, why now, who matters, and what to say.
→
ACCOUNT INTELLIGENCE
Account
Should we work this company? Why now? Who matters?
→
PERSON INTELLIGENCE
Person
Why this person? What do they care about? What should I say?
SIGNALS
Signals
What just happened that gives me a reason to reach out today?
✓Every verdict shows the four checks behind it: company size, industry, buying committee, momentum. Each check has its reason, and every suggested angle cites its sources.
What it replaces
LinkedIn prospect research in one run
company page→employee search→six profiles→recent posts→job listings→a notes doc
One report run replaces the whole chain.
Account Intelligence
Paste a company LinkedIn URL.
Fit
Momentum
People
Context
A database record gives you industry, headcount, and titles. This tells you whether to call, who, and why now.
A verdict with four states
Pass, Investigate, Fail, or Insufficient data. Investigate is a feature: it tells you exactly what to check before you commit the account.
Firmographics and momentum
Industry, headcount and HQ, then what’s moving: 6-month, 1-year and 2-year growth, function-level growth, open roles, and new hires by month with senior hires broken out.
Disposition reasoning
One plain-English sentence plus four checks: company size, industry, buying committee, momentum. Deterministic: the same inputs always produce the same verdict. Momentum can flip it; shrinking headcount downgrades a would-be pass to “verify budget first.”
Buying committee
Up to 15 people, Director level and above by default. A broader search backfills when your ICP surfaces too few. Each member shows how they matched, their live signals from the last 90 days, and a one-click person run.
Recent company posts
The company page’s last month of posts, with engagement counts and links.
It shows every check it ran, and why each passed or missed.
← Intelligence
Northwind Analytics
● PassAccount Intelligence · Run by sdr@northwind-analytics.example.com
Firmographics
IndustrySoftware Development
Employees182
HQDenver, CO, US
AboutSee the pipeline you actually have.
Northwind builds pipeline analytics for B2B revenue teams, forecasting, attribution and CRM hygiene in one place, so the number you walk into Monday with is the number you close.
Northwind builds pipeline analytics for B2B revenue teams, forecasting, attribution and CRM hygiene in one place, so the number you walk into Monday with is the number you close.
Company momentum
Headcount
182
6m growth
+9%
1y growth
+21%
2y growth
+48%
Median tenure
2.4y
Function growth (1y)
Sales41
+37%
Marketing18
+12%
Engineering64
+9%
Revenue Operations11
+22%
Open roles by function
Sales
6
Engineering
4
Revenue Operations
2
New hires by month
Sep 252
Oct 253
Nov 252
Dec 254
Jan 263
Feb 262
Mar 265
Apr 264
May 263
Jun 266
Jul 264
Aug 265
SENIOR HIRES
Disposition reasoning
Strong ICP fit: 5 committee members and firmographics match your target profile.
✓Company size182 employees, inside your 5–5000 band
✓IndustryLinkedIn: “Software Development” · matched your “B2B SaaS”
✓Committee5 members (2 title · 2 function · 1 seniority)
—Momentumheadcount grew 21% over the last year
Buying committee · 5
✦ Run intelligence on all (3)ML
Maya Lindqvist
VP Revenue Operations
Title match3 signals · last 90 days
Denver, Colorado, United States
View intelligence →Role context ⌄
DO
Daniel Okafor
Director, Sales Operations
Title match
Denver, Colorado, United States
✦ Run Person IntelligenceRole context ⌄
PP
Priya Patel
Head of Data Platforms
Function match
Boulder, Colorado, United States
✦ Run Person IntelligenceRole context ⌄
TN
Tom Nguyen
Chief Revenue Officer
Seniority match1 signal · last 90 days
New York, New York, United States
View intelligence →Role context ⌄
ER
Elena Rossi
Senior Manager, RevOps Analytics
Function match
Chicago, Illinois, United States
✦ Run Person IntelligenceRole context ⌄
Reasons you can read
Every verdict shows its work: four checks with what each one found, in plain English. When it says Pass, you know why. When it says Investigate, you know what to check.
Disposition reasoning
Strong ICP fit: 5 committee members and firmographics match your target profile.
✓Company size182 employees, inside your 5–5000 band
✓IndustryLinkedIn: “Software Development” · matched your “B2B SaaS”
✓Committee5 members (2 title · 2 function · 1 seniority)
—Momentumheadcount grew 21% over the last year
Momentum at a glance
Headcount, growth over three horizons, and which functions are actually expanding, so you can tell a company that’s scaling into your pitch from one that’s coasting.
Company momentum
Headcount
182
6m growth
+9%
1y growth
+21%
2y growth
+48%
Median tenure
2.4y
Function growth (1y)
Sales41
+37%
Marketing18
+12%
Engineering64
+9%
Revenue Operations11
+22%
Open roles by function
Sales
6
Engineering
4
Revenue Operations
2
Hiring, month by month
Twelve months of new hires with senior hires broken out. A cluster of senior hires is a budget being spent. Call now, not next quarter.
New hires by month
Sep 252
Oct 253
Nov 252
Dec 254
Jan 263
Feb 262
Mar 265
Apr 264
May 263
Jun 266
Jul 264
Aug 265
SENIOR HIRES
The buying committee
Stop wasting time filtering a contact database. Use a live search of who works there today, matched to your ICP.
Every member is verified to work at the company today, then deduped. Parent-brand aliasing is handled. Each row shows the reason it made the list: title match, function match, or seniority match.
From here, one click runs Person Intelligence on a member, or on the whole committee at once.
Buying committee · 5
✦ Run intelligence on all (3)ML
Maya Lindqvist
VP Revenue Operations
Title match3 signals · last 90 days
Denver, Colorado, United States
View intelligence →Role context ⌄
DO
Daniel Okafor
Director, Sales Operations
Title match
Denver, Colorado, United States
✦ Run Person IntelligenceRole context ⌄
PP
Priya Patel
Head of Data Platforms
Function match
Boulder, Colorado, United States
✦ Run Person IntelligenceRole context ⌄
How each person matched your ICP, with the receipt
Already have the person’s name? Start here.
Start from just the name. An inbound lead you’ve never heard of, a demo request from an unfamiliar company, an event attendee, someone thoughtful in a competitor’s comments: paste the profile and get the full read before you reply.
Person Intelligence
Paste a LinkedIn profile URL.
Weeks of someone’s LinkedIn activity, read for you: what they post about, what’s a signal and what’s noise, and the angle that cites its sources.
The read before you read
Flags up top: hiring, open to work, recent job change. Then the signal count, activities analyzed, a deterministic activity score out of 100, and a confidence indicator that says “Limited context” when evidence is thin.
Signal vs noise, week by week
An 8-week chart that splits signal-qualifying activity from everything else, over three LinkedIn pipelines run in parallel: their posts, their comments and reactions, their reposts. Up to 80 recent items, each qualified individually.
A digest that cites its sources
3–5 bullets synthesizing their whole recent footprint, topic tags from a fixed taxonomy, and a suggested angle with citation chips linking to the actual posts behind it.
Qualified signals, explained
Every signal carries its qualification reason in plain English, a strength score out of 10 on the same scale as your Signal Inbox, and a link to the source post.
← Intelligence
Maya LindqvistHiringRecent job change
● CONF 0.94VP Revenue Operations · Run by sdr@northwind-analytics.example.com
2 signals · 51 activities analyzed Activity 72/100 · active
Summary
Northwind Analytics sells pipeline analytics to B2B revenue teams. Companies like this typically buy forecasting and data-quality tooling to support GTM planning, so treat this person as a potential buyer.
Employer business model
Northwind sells pipeline analytics for B2B revenue teams, forecasting, attribution and CRM hygiene in one place.
Why this person
Surfaced in the buying committee for Northwind Analytics because her title matched your target titles: VP Revenue Operations.
As VP Revenue Operations at a 182-person company growing sales headcount 37% in a year, Maya is likely accountable for forecast accuracy while the pipeline scales. Northwind’s own pitch, “see the pipeline you actually have”, makes honest forecasting and CRM hygiene an executive-level concern, and her hiring of two RevOps analysts suggests the team is building capacity for exactly that work.
Given Northwind’s focus on making pipeline visible and this year’s sales growth, I thought it would be relevant to connect on how your team keeps the forecast honest while headcount scales.
⧉ Copy openerActivity digest
●Forecast accuracy and CRM hygiene are her recurring themes; she names specific fixes, not vendors.
●She comments more than she posts, and replies on RevOps threads within a day.
●Actively recruiting: hiring two RevOps analysts in Denver and asking her network for referrals.
●Engages with adjacent topics, attribution, pipeline reviews and forecast rituals, mostly on others’ posts.
💡
Suggested angle: Open with her post on the forecast that was wrong two quarters running, she traced it to a single CRM field and offered to share the cleanup doc. Ask for the doc, then connect that cleanup to keeping the forecast credible while sales scales.
post 1 ›post 2 ›comment 3 ›reaction 4 ›reaction 5 ›
Pain-point · 4Hiring-signal · 2Migration-switch · 1Thought-leadership · 1
Signals · 2
PostQualifiedStrength 8/10~9 days
I went back through our forecast reviews from the last two quarters. The number we walked in with was wrong both times, and both times the cause was the same CRM field. We fixed the field, not the dashboard…
The post is directly about forecast accuracy and CRM hygiene, the exact pain a pipeline-analytics buyer feels, and is likely to engage RevOps leaders at B2B software firms.
View post on LinkedIn ↗👁 View Signal➤ Push to Inbox
PostQualifiedStrength 7/10~16 days
LinkedIn network, we’re hiring two RevOps analysts in Denver. If you know someone who loves clean CRM data more than they should, my DMs are open…
This hiring post signals active RevOps team expansion, making likely engagers relevant practitioners even though the content is primarily recruitment-focused.
View post on LinkedIn ↗👁 View Signal➤ Push to Inbox
Profile
CompanyNorthwind Analytics
LocationDenver, Colorado, United States
LinkedInProfile page ↗
HeadlineVP Revenue Operations at Northwind Analytics · I make forecasts honest
Activity
72active · Jun 29–Aug 17
Jun 294
Jul 65
Jul 136
Jul 207
Jul 277
Aug 39
Aug 108
Aug 174
SIGNAL-QUALIFYINGOTHER ACTIVITY+1 UNDATED
50 in the last 8 weeks
F2 · A person report
Openers built from what they actually said. Every angle cites its posts.
✓The digest reads weeks of posts, comments and reactions for you: 3 to 5 bullets on what this person actually cares about.
✓The suggested angle is grounded in their own words. Citation chips link to each post behind it, so you can read the source before you write.
✓Topic tags show the themes they keep returning to, with counts. No guessing what will land.
Activity digest
●Forecast accuracy and CRM hygiene are her recurring themes; she names specific fixes, not vendors.
●She comments more than she posts, and replies on RevOps threads within a day.
●Actively recruiting: hiring two RevOps analysts in Denver and asking her network for referrals.
●Engages with adjacent topics, attribution, pipeline reviews and forecast rituals, mostly on others’ posts.
💡
Suggested angle: Open with her post on the forecast that was wrong two quarters running, she traced it to a single CRM field and offered to share the cleanup doc. Ask for the doc, then connect that cleanup to keeping the forecast credible while sales scales.
post 1 ›post 2 ›comment 3 ›reaction 4 ›reaction 5 ›
Pain-point · 4Hiring-signal · 2Migration-switch · 1Thought-leadership · 1
Every angle cites the posts behind it
From research to a reason
Research becomes a prospecting event
Any qualified signal opens in the standard signal detail view and pushes into your Signal Inbox, and from there into Slack or webhook delivery. Free.
Research stops being a doc you wrote and becomes an event in the workflow you already run: Always On Signals & Monitoring →
Signals · 2
PostQualifiedStrength 8/10~9 days
I went back through our forecast reviews from the last two quarters. The number we walked in with was wrong both times, and both times the cause was the same CRM field. We fixed the field, not the dashboard…
The post is directly about forecast accuracy and CRM hygiene, the exact pain a pipeline-analytics buyer feels, and is likely to engage RevOps leaders at B2B software firms.
View post on LinkedIn ↗👁 View Signal➤ Push to Inbox
A qualified signal, explained. One click from your inbox
Check the work and understand the reasoning.
01
The four checks behind every verdict
Every account verdict shows the four checks it ran: company size, industry, buying committee, momentum. Each check carries its reason.
02
A qualification reason on every signal
Plain English, next to the signal, with a link to the source post it came from.
03
Citation links on every angle
The suggested angle carries chips to the actual posts behind it. Click and read what they wrote.
Cost & plans
Same credits as everything else
~12 credits
per account report
~31 credits
per person snapshot
Free
re-runs within 30 days (cached), pushing signals to your inbox, role context and the digest
Included on Trial, Pro, and Scale; Solo skips it. It draws from the same credit pool as monitoring, and the REST API and MCP tools run it at the same prices. See pricing →
Ditch the list of 500 contacts.
Start your day with qualified accounts, updated buying committees, and people with live signals.
Start your day with qualified accounts, updated buying committees, and people with live signals.