B2B demand-detection engine · Madrid

B2B demand generated by a system, not by luck.

A worker in production cross-references six signal sources every month, finds accounts with real pain and attaches the evidence — url and date — of why they fit. You decide who to approach.

Try the engine with your domain →Let's talk

Worker in production · monthly refresh

No bought lists. No opaque scraping.

Resumen rápido

Píldora Digital's B2B detection engine cross-references six public sources (GitHub, Hugging Face, LinkedIn, AWS re:Post, Crunchbase, job boards) every month to find deep-tech, regulated or professional-services accounts with real buying pain. Every account arrives with cited evidence — url and date — never an unsourced claim.

6 sources

Active signal sources, cross-referenced per account

Monthly

Index refresh. Worker in production

100%

Accounts with cited evidence: url + date

7–10 days

From signature to production, not signature to kickoff

Where the signal comes from

Six public sources, cross-referenced per account.

Every claim the system makes points to a url with a date — you can audit it.

GitHub

technical activity

Hugging Face

models and datasets

roles and growth

AWS re:Post

stack pain points

Crunchbase

funding

Job boards

hiring

The system

One engine. Five fronts.

Data discovers and qualifies. Content evangelizes. Outbound and ads capture. Remarketing closes the loop. Each front lifts the conversion of the next.

01 · Data

Signal engine

Finds accounts with real pain and qualifies them with cited evidence: hiring, funding, tech stack, technical activity.

02 · Content

Evangelization

Technical pieces that build the conversation where your buyers live and disarm the credibility objection.

03 · Outbound

Email + LinkedIn

Sequences segmented by the reason to buy, not spray-and-pray. 1:1 for strategic accounts.

04 · Paid media

ABM + intent ads

LinkedIn to the exact accounts and roles; Google for active search; awareness where the narrative is missing.

05 · Loop

Remarketing + CRM

Retargeting by funnel stage and a monthly loop that re-learns: the system improves itself.

Qualifying an account is this simple:

Engine demo · example

Try the engine. Drop in a domain.

Illustrative example

This is how the sales team sees a qualified account.

Mockup with fictional data — the account "Vectorpath AI" doesn't exist. Not a real screenshot of any client.

Accounts

Vectorpath AI92

Nordhaus Legal Tech87

Cerebra Health81

Kalman Robotics78

Fintel Compliance74

Vectorpath AI

Fit score 92

Deep-tech / AI infra · Madrid · 48 employees

Signals with evidence

3 new LLM-inference repos in 60 days · last commit 4 days ago

GitHubgithub.com/vectorpath-ai/vector-serve· 22 Jul 2026

2 open roles: ML Platform Engineer · MLOps

Job boardscareers.vectorpath.ai/ml-platform· 18 Jul 2026

Open question about production inference latency

AWS re:Postrepost.aws/questions/vectorpath-inference-latency· 11 Jul 2026

Series A of €14M closed, declared use of funds: data infrastructure

Crunchbasecrunchbase.com/organization/vectorpath-ai· 02 Jul 2026

Why it fits

They're building inference infrastructure with an in-house team and recent funding. They buy technical credibility, not lead promises.

Verticals

One engine, several verticals.

The same engine adapts to the reason to buy of each deep-tech vertical. Pick yours.

[PENDIENTE: IMG-B2B-DEEP-TECH-IA] 1200×800 — Vertical — Deep-tech and AI

Deep-tech and AI

The signal is in the repo, the stack, and who they're hiring.

[PENDIENTE: IMG-B2B-REGULADO] 1200×800 — Vertical — Legal, health and finance

Legal, health and finance

Domain accuracy and reputational risk, not lead volume.

[PENDIENTE: IMG-B2B-SERVICIOS-PROFESIONALES] 1200×800 — Vertical — Firms and consultancies

Firms and consultancies

Pipeline without building a sales team.

Trust

“If it can't be cited, it isn't stated.”

Only public, auditable sources

No bought lists, no untraceable third-party data. Every signal links to its origin.

Your data trains nothing

What you give us is used for your account and nothing else. Per-client isolation on the platform.

Cited evidence, always

Every claim the system makes carries a url and a date. If it can't be cited, it isn't stated.

To read before the call.

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Try the engine

Give us your domain. We hand back accounts with evidence.

We run a real detection pass over your customer profile and show you the accounts with their cited signals. No one-hour demo.