Outricher · AI data search

Your next outreach list.Researched and prioritized for you.

Any ICP, found in 800M+ professional profiles.

Tell us who you want to reach or what you’re trying to achieve. We combine signals such as career history, job changes, funding and hiring to build your list. You get matching contacts, ranked by fit, with a clear reason for each match.

800M+ professional profiles · 130+ fields per contact, career background and recent posts included

Get a free research →Book an intro call

The research is free. You pay only for the rows you take.

ICP search

›Java and Scala engineers with live open-source activity on data platforms

scored hot
signal fired
fits the ICP

Filters, combined800M+ profiles → 21,713 matched

public coderepos ∋ {Flink, Spark, Trino}

career historypast_companies · tenure

contactspersonal email

Staff Software Engineer

Stream processing · Scala

Flink contributor9 yrs · 3 companies

Senior Data Engineer

Query engines · Java

Trino contributorpersonal email

✓ 21,713 candidates · 134 fields eachdelivered in one day

Your own outreach list and the research behind it — for less than the data costs on the market.

Your outreach list

People who match your parameters across 130+ fields, ranked by fit, with the reason for every match and the contacts to reach them.

Your research

The market behind the list: how big it is, how it splits, who buys and where to start. Free.

A list ofcustomersinvestorshirespartnersyour competitors’ customers

Start here

Tell us who you want to reach — the research is free, you pay only for the rows you take.

Write to us →Book an intro call

or write to hi@outricher.com

One row of your list · illustrativewhat clients use most

Person: Head of Sales · Series A logistics tech
Fit: 94 / 100
Why now: new role 2 months ago · the company raised 4 months ago
Recent posts: wrote about rebuilding the SDR team
Background: 9 years · 3 companies
Company: 120 people · hiring SDRs
Contacts: work email · personal email · social profiles
And: 130+ fields in the file

Then it runs as a loop — your lead-gen and outreach machine.

01 Findwho fits, ranked, with the reason
02 WriteAI writes to each from 130+ fields, on their channel
03 TestA/B segments and messages on a small slice
04 Expandlook-alikes of who converted — round again ↻

ResearchfreeRowspay only for the ones you takePricebelow what the same data costs on the market

What you can do

Find people by ICP

Heads of Finance at 50–500-person companies in the UK

A scored list, the reason on every row.

Catch the moment

Who started a new role in the last 90 days?

new role ≤ 90 d×fits ICP

Signals joined: who is ready to talk this month.

Profile your audience

Who actually buys from us?

titlesizestage

A portrait from your CRM: roles, companies, careers.

Find a new audience

Who looks like our best customers — and is not one yet?

your CRM›look-alikes

Look-alikes across the market, scored by closeness.

Research an ad direction

Which segment should the ad budget go to first?

test firstnextskip

Audience lists by segment, ready for the ad platforms.

Get a free research

How big is this market, and where do we start?

hotwarmcold

Market size, segments and a report — free.

Validate a concept

Is there a market for this idea — and who would buy first?

one segment›real replies

A sized segment and a test slice, before you build.

Reach out, get feedback

Write to them — and tell me what they answer.

sentreplycall

First lines written from the record; replies rescored each round.

01The data

One stitched record per person. 130+ fields.

Not an email and a title: the whole history of a person — work, education, code, posts — cross-checked across sources and refreshed continuously.

Identity & contacts

full name
headline
location
personal emails
work email
phones
social profiles
website

Education, skills & languages

schools
degrees
fields of study
class years
skills
languages
certifications

Career history

every position, dated
title & seniority
tenure
employer per role
role changes
first 90 days flag
past employers
career path

Activity & posts

recent posts
profile updates
open-to-work signals
activity recency
topics they write about

Current company

size
industry
HQ
funding rounds
investors
open roles
hiring velocity
tech stack

Public code

repositories
languages
contribution activity
open-source projects

800M+

current profiles, refreshed continuously

400M+

with personal contacts

Hours

from a request to a scored export

from $0.03

per full profile — about 5× below Clay-class tools. The research is free.

Open the field-by-field walkthrough of a real record →

02Look-alike audiences

Start from the customers you already have.

Send the emails your CRM has. We enrich every customer to the full record, find the personas your buyers fall into — and bring back the people on the market who look like each of them.

01Send

The list you already have

Emails, domains or names. Nothing else is required.

1,245rows · one field each

your export

m•••@brightlane.io
k•••@northfork.co
a•••@quillbase.com
d•••@lumenpay.app
r•••@tessel.ai
+ 1,240 more

02Enrich

Every row becomes a full record

Career, company, skills, signals, contacts — per customer.

130+fields per person

k•••@northfork.corow → record

Title: VP Sales
Company: Series A · 120 people
Career: ex-operator · 2 startups
Signal: new role · 4 months
Contacts: personal email · phone

contactscareerskillscompanyactivitycode130+ fields

03Segment

Your buyers fall into personas

The ICPs are found in your own data, not assumed up front.

3personas in this CRM

found in your CRMshare of customers

ASales leader at a funded startup46%VP / Head of Sales · Seed – Series B
BFounder who still sells33%Founder / CEO · under 20 people
CRevOps builder21%RevOps / Sales Ops lead · 100–500 people

04Find look-alikes

Each persona finds its look-alikes

A model on 130+ fields and signals scores the whole market against each persona.

6,312new people · not in your CRM

closest on the marketmatch

AVP Sales · Series A logistics tech94%
BFounder & CEO · 12-person fintech91%
CHead of RevOps · Series B HR tech88%
AHead of Sales · seed devtools85%

1,245 customers in → 6,312 look-alikes out · 71% with a verified email

Start from my CRM →Book an intro call

Illustrative run — the personas and the matches are built from your CRM, not from a template.

03Custom datasets

Two ways in. One free research. You pay for rows, not for work.

A finished ICP or just a business problem — the research runs across the whole market before you spend anything.

No ICP yet

Tell the AI what you sell and who buys it today. It drafts the ICP with you — segments, signals, exclusions.

we shape it together

ICPs in hand

Hand them over as they are — a paragraph, a spreadsheet, a boolean string. The AI asks only what it cannot infer.

hand it over as is

Free research

Everyone matching, across the market — not a sample.

audience size
segment list
signal check

free

Scored & grouped

Ranked against your ICP, split into segments, each row with its evidence.

score per row
hot · warm · cold
reason per match

free

Analytical report

Sizes, portraits, the hottest groups, what to test first. Yours to keep.

report.html
charts & portraits
what to test first

free

The rows you take

That is the only thing you pay for — the count you choose, with contacts.

leads.xlsx · csv · json
contacts verified
CRM-ready

the only paid step

Start here — it costs nothing

Write who you need in a line. We come back with your market, sized.

A free consultation — a reply within one working day
Sizing, scoring and the report — free, yours to keep
The dataset from $0.03 a row, only the rows you take

Book an intro call

Describe it briefly — get a free research

04Signals · what you can find

Moments of need, not job titles.

A title says who someone is. A moment says who is ready to talk this month. Pick a task.

outricher · ai data search13 sources · one record

›find people who use my competitor's product

They already have the budget and the habit — the conversation is about switching, not about the category.

Joined for this task

1skills ∋ "product"skills
2role_text ∋ "product"role description
3title ∈ your ICPorg & level

Then the AI analyst runs

ICP drafting
Market sizing
Scoring
LLM judge
Audience portrait

careercompany & fundinghiring & activityorganisation

You get

Every user with role, seniority and a personal email — plus the portrait of who that product sells to.

All filters combine — and every contact comes with the evidence for why it made the list.

Get this for my market — free →Book an intro call

05Depth

Nine things a catalogue architecturally can't hand you.

Our own index, with joins across sources that catalogues keep in separate tables.

01Cross-signal triggers

Combine signals that don't work on their own

Funded, hiring SDRs, no VP Sales yet: a buying moment that exists only where three sources agree.

1,479 leaders · 86% emails — a delivered case

02Negative search

Search by what is not there

No VP Sales, no tool in the stack, no posts for three months. Here an absence is a filter.

3,847 senior ICs to recruit

03Career history · 5.6B positions

Search by who a person used to be

Every position is kept and dated, so a filter can take one seat from the past and one from today.

287 ex-rocket engineers turned investors

04Signal recipes

Build an audience nobody lists

A foreign degree, a US job, under seven years in the country: three plain facts, one segment no catalogue sells.

11,500 profiles · reordered 10× in six months

05Snapshots

Ask what changed since last month

Any two dates compare: who joined, who left, who was promoted, which teams grew.

your market on two dates, row by row

06Signals over time · weekly feed

Search by what just changed

A new seat, a round, a burst of hiring — run every week as a feed over your ICP.

every week: who to write to, and why

07Signal library

Signals from every layer of the record

Job changes, rounds, hiring bursts, tenure windows, public code, a missing role — each a dated fact. Yours can be added.

four families · 13 sources joined in one record

08Evidence

Every match carries its reason

The signal, its source and its date travel with the row — into your CRM and your first line.

the reason to write arrives with the row

09Bulk + scoring

10,000 contacts in one export — already scored and segmented

Sorted by score for your ICP and cut into ready segments.

ready for outreach, not raw fields

Your search, written as a query.

Send the case — we write it, run it across the market and size it. Free.

Get a free research →Book an intro call

06Proof

What it did for clients.

Reply and conversion rates our clients reported, against the baseline they had before.

with Outricher datatheir usual baseline

Sales outreachreply rate

8–15%vs 1–2%

Founders of funded startupsmeeting conversion

11%vs 1–2%

Negative-search pilotreply rate

8%vs 2%

Job seekersapplication-to-interview conversion

15–25%vs 2–5%

Recruitingreply rate, personal email vs in-platform messages

25–40%vs 10–15%

Three clients, three briefs — and what each one left with.

Delivered work, told the way the client experienced it: what they asked, how we solved it, what was handed over and where it runs now. Every card opens the full study.

300day-one wave, with email

1 in 72 made the day-one wave · 1 day from brief to handoff

21,713candidates mapped
3,300ranked for outreach
25confirmed twice

Recruiting · engineering talent

The brief

“Data-platform engineers in the Bay Area, open-source contributors preferred.”

— Adobe

Two search strings the recruiting team had been running by hand, with a quarter of sourcing ahead of them.

How we solved it

Ran the brief two ways in one day: from public code to the person, and from career history back to the code.
Track one found who is visibly committing to Flink, Spark, Kafka and Iceberg; track two kept open source as a weight, not a wall.
Where the two tracks agree is the shortlist nobody else can see — ranked by fit and reachability into three waves.

Handed over

21,713 candidates, 134 fields each, with the reason for every pick
three outreach waves ranked by fit and reachability — 300 on top for day one
25 engineers confirmed by both methods, each with email and full career history

A week of outreach ready on day one: 300 people ranked first, every one with an email and the reason for the pick.

The same brief ran again on fresh data five months later — the same two tracks, a new wave of contacts.

Study the case →

10×the best one reordered

six months · ten orders of the same segment · 98.9–100% email coverage

19,470+profiles delivered
6client profiles

Immigration law · client acquisition

The brief

“Foreign nationals who will file for O-1, EB-1A or EB-2 NIW this quarter.”

— A US immigration law firm

Not engineers in California — the few hundred whose status window is closing right now.

How we solved it

Keywords fail here: of 13,926 founders, nine mention visa intent anywhere public.
So we built six client profiles from the shape of a career — a degree earned abroad next to a job held in the US, under seven years in the country, a founder title that switched last month.
Every match ranked by how fresh the signal is, with the evidence on the row.

Handed over

19,470+ ranked candidates across six client profiles
the signal, its source and its date on every row
98.9–100% email coverage on every shipped cut

The firm stopped buying lists and started ordering the slice: a paragraph in, a ranked file out.

A standing order: the best profile was reordered ten times between March and August, each time against a fresher market.

Study the playbook →

6reports in two days

two days from the company name to six reports · 45 people · 17 countries

1company, public data
8audience profiles
115candidates, 4 roles

Market research · consumer fintech

The brief

“What can you tell us about our own company — and who should we be talking to?”

— Brighty, a crypto-fiat neobank

No access to internal systems; public data only.

How we solved it

Public data only: the company, its people and its hiring reconstructed from the outside.
The AI analyst built six reports in two days — the team by name and origin, six years of company history, the gaps in the structure.
Eight audience profiles, each verified against live data, and candidates for the roles they could not fill.

Handed over

six reports, each with the dataset it was built on
8 audience profiles — users at competitors, crypto earners, relocants — each a reachable pool
250 funded fintechs for the B2B pipeline and 115 candidates for 4 open roles

The company and its customers as the market sees them — and the lists to reach both, users at competitors and the B2B accounts worth a call.

The run is repeatable for any company: the same six reports and the audiences behind them, refreshed on request.

Study the research →

07Beyond the dataset · putting the data to work

The data is the floor. We build the pipeline that runs on it.

What the strongest GTM teams run today — multi-layer sourcing, signal-based outreach, AI research on every lead — set up inside your company, on our data.

Why now

Outbound moved from lists to reasons. The teams that win run a system, not a campaign.

2–5×

the replies a message with a reason draws, against a generic one

5–15

data layers a modern team chains to cover one segment

4–6 weeks

from kickoff to an outbound system your team owns

Market figures for 2025–2026; the timeline is our standard build.

What we set up

01 Multi-layer sourcing

Our record, your CRM and extra layers in one list — deduplicated, scored, verified.

one list — no duplicates, contacts verified
a score and the reason on every row

data

02 Signal feed

Every week: who changed jobs, raised a round, started hiring.

a fresh list every week
the reason to write, dated

timing

03 AI research per lead

An agent reads the profile and the signal and drafts the first line.

one template, four slots: reason, problem, proof, ask
no two first lines repeat

AI + people

04 Sequences & channels

Email, social and ad audiences from one segment; deliverability watched daily.

every channel, the same segment
domains warmed, limits and bounces watched

outreach

05 Replies → CRM → rescoring

Replies land in your CRM; scores and copy move with the evidence.

a dashboard of replies and meetings by segment
the winner scaled, the rest rebuilt

feedback

↺ runs every week · each round sharpens the nextHanded overthe playbook · the dashboard · API + MCP in your stack

How we work with you

How we work

Set up in-house

Built in your stack, handed over with the playbook.

How we work

Run as a service

We run it — you take the meetings.

How you pay

Fixed price

A scoped build with a deadline.

How you pay

Commission

A share of the result: we earn when you do.

We set the whole chain up, or plug any part of it into what you already run. Most clients arrive with one task and leave with three.

Get a plan — free →Book an intro call

How we work · result as a service

You pay for the outcome.Not for access to data.

Result as a service: a brief goes in, a measured result comes out — the list, the research and the system that keeps producing them.

A case, worked to the result
Not a seat in a tool. We take the brief to a shortlist that converts, a market that is sized, a pipeline that fills.
Set up inside your company
Data flows, outreach and analytics automated in your stack and handed over with the playbook — so the result keeps coming without us.
No two cases alike
The method is ours; the configuration is yours. Adobe’s two tracks, the firm’s six profiles, Brighty’s six reports — each one built for the brief.

Yours is different too. Tell us about it — we will be glad to talk.

Write to us ↓

08Start here

Tell us who you need. The research is on us.

An ICP, a business case, a dataset or product access — we reply within one working day with the first sizing.

Sizing and research first, free
Nothing to pay until you take rows

Prefer to talk first? The call and the research are free either way.

Book an intro callpick a slot — an analyst, your case, a first sizing Write an emailhi@outricher.com Message on Telegram@outricher

09The product · private access

The same engine, in your hands.

A private product, opened by subscription. Your team gets a key to run the same searches, exports and analytics we do.

private product
by subscription
access on request

API

A profile, an email or a plain-language request in — ranked JSON out.

request in → ranked JSON out

MCP server

The whole toolset for any agent: plan, search, score, verify, deliver.

your agents, our record

Claude plugin

Describe a case in Claude: it sizes it for free, then builds the list and the report.

a business case in → list + report out

Jev judge

Reads every row against your ICP — accept, review or reject — and gates only after a person checks it.

accept · review · reject

claude · outricher pluginprivate

›Foreign-educated AI engineers in the US, under seven years in the country — size it and build the list.

planhypotheses sized: population per country, email share, costfree
search → scorerows scored against the ICP, the reasons attached
judgeevery row read; doubtful ones sent to review
reviewyou check a sample — the judge gates only after a person agrees
verifyfull profiles and verified contacts for the accepted rows
deliver → reportleads.xlsx · csv · json · report.html

✓ nothing is spent until you confirmcounting and planning are free

Access opens per team: a call first, then a key and a quota to test on your own case.

Built with these tools: the visa ICP playbook →

Request access →Book a product demo

Your next outreach list.Researched and prioritized for you.

Your own outreach list and the research behind it — for less than the data costs on the market.

Your outreach list

Your research

Find people by ICP

Catch the moment

Profile your audience

Find a new audience

Research an ad direction

Get a free research

Validate a concept

Reach out, get feedback

One stitched record per person. 130+ fields.

Identity & contacts

Education, skills & languages

Career history

Activity & posts

Current company

Public code

Start from the customers you already have.

The list you already have

Every row becomes a full record

Your buyers fall into personas

Each persona finds its look-alikes

Two ways in. One free research. You pay for rows, not for work.

No ICP yet

ICPs in hand

Write who you need in a line. We come back with your market, sized.

Moments of need, not job titles.

Nine things a catalogue architecturally can't hand you.

Combine signals that don't work on their own

Search by what is not there

Search by who a person used to be

Build an audience nobody lists

Ask what changed since last month

Search by what just changed

Signals from every layer of the record

Every match carries its reason

10,000 contacts in one export — already scored and segmented

Your search, written as a query.

What it did for clients.

Three clients, three briefs — and what each one left with.

Two boolean strings in. Monday morning’s 300 out.

Six kinds of client, each caught while the status clock is running.

A company studied from the outside: team, customers and hiring in two days.

The data is the floor. We build the pipeline that runs on it.

Set up in-house

Run as a service

Fixed price

Commission

You pay for the outcome.Not for access to data.

A case, worked to the result

Set up inside your company

No two cases alike

Tell us who you need. The research is on us.

The same engine, in your hands.

API

MCP server

Claude plugin

Jev judge