Outricher · Business Capabilities Overview
Intelligence for every outreach

Know who to reach, how to reach them,
and exactly when.

Outricher turns a living graph of 1.17 billion professional profiles into ranked targets, personal contact data, and real-time momentum signals — so your team, or your AI agent, never sends another generic, mistimed message.

1.17B
Professional profiles, continuously refreshed
237M
With personal email & phone on file
47
Data fields per profile, one API call
~$0.02
Per enriched contact — discovery is free
The problem

Outreach fails for two reasons — and both are data problems.

You reach the wrong person, or you reach the right person at the wrong moment. Static lead lists can't fix either: they're a frozen snapshot, stripped of the context that makes a message land and blind to anything that just changed.

Wrong target

Generic lists match a job title, not a thesis. The decision-maker who actually fits gets buried among hundreds who don't.

Wrong moment

A name tells you who someone is. It can't tell you they just raised, just changed firms, or just started hiring — the only thing that makes timing right.

No personalisation

Without a personal channel and real context, even a perfect-fit, perfectly-timed message reads like a template — and gets ignored.

The solution

One data engine. Three things no list can do.

Because Outricher is a connected graph — people linked to roles, companies, funding, and code — it answers questions a spreadsheet never could. Everything below runs on the same engine.

1

Rank by fit

From a universe of millions down to the few dozen who match your stage, geography, and thesis — each a named human.

2

Reach in person

Personal email, phone, social handles, recent posts, career arc — the raw material for a message that sounds human.

3

Time it right

Funding, role-change, and hiring signals computed from data the company hasn't announced yet.

What it does — six business capabilities

From raw question to revenue-ready action.

Every chart below is real, queried live from the production dataset. The cases are illustrative — the data is not.

01 · Investor & lead discovery

Ranked target lists that refresh themselves

Define your ICP once — stage, geography, thesis. Outricher isolates the matching universe from 17,227 venture & PE firms and ranks it down to the named partners who actually fit, re-running weekly so your pipeline never goes dry.

  • Thesis-matched, not title-matched
  • Named individuals, never info@
  • Auto-refreshed on your cadence
17,227 → 30From the full universe down to the partners worth your agent's time — automatically.
Venture & PE firms by team size. The boutique long tail (1–10) is where under-marketed, thesis-specific partners sit.
35% of senior investors already carry a verified personal email at zero cost. You pay only for the rest, only when you choose to reach them.
02 · Contact enrichment

The personalisation layer, one call away

Hand us a name or a profile and get back a 47-field dossier: personal email, phone, social handles, recent activity, and full career history. A real live pull on a public investor returned 11 personal emails, an X handle, and a clear role change to lead with.

  • Personal channels, not corporate switchboards
  • Career arc → a credible human opener
  • One third of senior contacts are free
2% → 20%The reply-rate gap personalisation closes — and exactly what an agent can't invent on its own.
03 · Founder intelligence

From a code repository to a warm email

When a deal scan surfaces a company through its open-source work, we resolve the founder to a full profile — personal email, dev activity, education, prior startups, time-in-role — drawing on 204M developer profiles linked to the professional graph.

  • Rank a repo's contributors by seniority in seconds
  • Reference real code & prior exits, not "I see you build tech"
  • Reach the builders who ignore generic VC outreach
days → 1 callThe collapse from manual founder research to an instant, credible, contextual dossier.
Hireable developers with real output, by following (log scale). The thin top bands are where founders cluster.
Quarterly hiring at two frontier AI labs, 2023→2026. The upward bend is visible quarters before metrics go public.
04 · Momentum signals

Reach them at the moment, not after it

Outricher flags the three timing signals that beat any target list: a company that just raised, an investor who just changed firms (open in their first 90 days), and a team that's suddenly hiring fast — a product that's working.

  • Funding signal, fresh with amounts & backers
  • Role-change cohort — named, dated
  • Hiring velocity — computed, not announced
2–3 quartersHow early a momentum signal surfaces vs. the public announcement. Timing is the edge.
05 · Portfolio monitoring

An early-warning feed on your holdings

The same signal engine, pointed at your portfolio and run on a schedule. Net headcount, key-person churn, and function-level ramps — surfaced weekly, with names, before they reach a board deck.

  • Headcount delta & hire:exit ratio per company
  • Founding-team departures flagged the week they happen
  • "First sales hire" and other growth signals
6 weeks earlyCatching a founding-team departure before the quarterly can change a reserve decision.
Trailing-12-month hires vs departures. A healthy company runs a high ratio; compression toward 1:1 is the early warning.
Wealth & family-office entities by region (log scale) — MENA in amber, European hubs in blue.
06 · LP & capital discovery

Run your raise on the same engine

Swap the filter to family offices, HNWIs, and corporates. The allocator universe is large and well-covered in exactly the regions funds raise from — MENA and Europe — each resolving to named principals with the same enrichment behind them.

  • 330+ wealth entities in the UAE alone, named
  • Same pipeline as deal sourcing — one engine, two ICPs
  • Turns the most manual part of a raise into a query
1 engine, 2 jobsDeal sourcing and the LP raise run on the same data spine and the same agent.
Why it's different

A graph beats a list at the things that drive revenue.

What you needA static lead listOutricher
Match by thesis, not job titleTitle filter onlyThesis text + signals
Personal channel to reach someoneCorporate email, maybePersonal email, phone, socials
Know when to reach outNo timing dataFunding · role-change · hiring
Stay currentStale on arrivalContinuously refreshed
Cost to explore broadlyPay per rowDiscovery is free
The economics

Aligned with how you actually work.

Broad discovery is free. Precision contact is cheap. You pay only for the people you decide to pursue — so exploring a market costs nothing and a full outreach campaign costs the price of a coffee.

OperationCoversCost
Discovery · ranking · segmentation · all signalsBuilding every list, every workflowFree
Pre-enriched contact≈20% of the graph; 35% of senior investorsFree
Live profile enrichmentFull 47-field dossier, on demand~$0.02
A weekly pipeline of 5,000 targets costs effectively nothing. Enriching the 200 you actually contact costs ~$4.
Proven at scale

The engine has done this before.

Representative outcomes from past delivery work on the same infrastructure.

38,000
Decision-makers extracted & ranked from an 18,000-firm investor universe in a single build.
86%
Email coverage delivered on a funded-startup lead set — outreach-ready out of the box.
780
Funded startups flagged on a "first sales hire" growth signal in one pass.
Start here

See it on your own ICP.

Pick one workflow. We'll deliver a live sample of 250 ranked, enriched targets matched to your thesis — end to end — so you judge the quality on real output, not a promise.