Service / AI & Automation

AI,
done right.

AI applied where it frees real hours, orders your pipeline and speeds content production. No flashy demos, no decorative chatbots, no pitch-booth promises.

AI is a lever,
not a demo.

72%

of Spanish SMEs want to implement AI, but less than 15% have moved from looking at tools to automating processes with measurable ROI in under 90 days.

Reference

AI in Spanish SMEs Report · 2025

What we mean by applied AI

There are two ways to talk about AI in marketing. One is real AI: automations that reduce team hours, productivity in content and reporting, cleaner attribution and models that order your pipeline. The other is demo AI: a chatbot that looked good in the proposal and a generator that fills the blog with noise. Only one pays salaries.

What we do differently

We touch AI where there’s a measurable process behind.

What we build together

Automation that saves real time. No hype.

Five capabilities connected to each other. Not sold separately: combined by the process burning the most hours today, whose result you can measure.

01Workflows & CRM integration

Repetitive work doesn’t earn salary. Critical work lives inside your CRM.

We design n8n, Make or Zapier flows that connect your tools and deploy AI inside the CRM your team already uses (HubSpot, Salesforce, Pipedrive, ActiveCampaign): lead capture and enrichment, scoring, sales rep assignment, call summary, next-best-action and reporting. AI lives where your sales rep lives, not in another tab no one opens.

  • −n8n self-hosted, Make and Zapier flows
  • −Native AI agents in HubSpot/Salesforce
  • −Call summary and next-best-action
  • −Enrichment, scoring and reporting
02AI agents & conversational assistants

Agents that qualify, resolve and hand over with context.

AI agents trained on your documentation, catalog and real FAQs (RAG). They resolve first-level 24/7, qualify visitors by intent and role, and escalate to human with full captured context. Web, WhatsApp Business and Slack. No decorative bots with three canned answers.

  • −LLM trained on your data (RAG)
  • −Intent and role qualification
  • −Clean hand-off to CRM and sales rep
  • −Web, WhatsApp Business and Slack
03AI-assisted content

Briefs, drafts and variants with AI. Senior human review always.

AI pipelines that speed up research, briefing, first version and multi-channel variants of posts, emails and landings. Editorial judgment is set by a senior. AI moves boring work, doesn’t sign for you. Result: more production without losing brand edge.

  • −Automated SEO + GEO briefs
  • −Drafts with learned brand voice
  • −Variants for ABM and email
  • −Editorial audit before publishing
04Predictive analysis

Lead scoring, churn prediction and sales forecast.

Models using your real CRM, analytics and billing history to prioritize leads, detect churn signals before cancellation and project closes far more accurately than rep intuition. Where there is enough data, there is defensible decision-making.

  • −Lead scoring with real models
  • −Early churn alert
  • −Monthly pipeline forecast
  • −Prior data hygiene
05Dynamic personalization

Web and email that change by segment and behavior, no black box.

Landings that adapt to visitor sector, size and source. Emails that swap blocks by real on-site behavior. Explainable rules, editable by your team and traceable in CRM. Real personalization, not a platform that decides for you.

  • −Dynamic content on web and landings
  • −Email blocks by behavior
  • −Explainable, auditable rules
  • −Consent and GDPR by design

Before buying a tool

Clear on what you’d automate first? We do it in one hour.

Let’s talk →

How we work

Four steps. Zero hype.

Every AI project starts the same: first we map the real process and measure. Without that diagnosis, any automation is a bet, not a system.

01

Process mapping

We document how your real flow works today: input, steps, owners, tools and times. No map, no useful automation.

02

Impact prioritization

Hours-saved / error-cost matrix. We attack first what frees sales and marketing time in 60 days, not what looks most technological.

03

Progressive automation

We deploy one flow at a time, with human control at first. We scale only when the pilot proves real savings and the team trusts the system.

04

Savings and value measurement

Reporting with hours saved, cost per lead, cycle velocity and scoring accuracy. What isn’t measured isn’t maintained.

What you won’t find

What we DO NOT do.

In AI it’s easier to make a demo than to deliver something that works in production. These are the limits that let us work with real judgment, not hype.

  • ×

    We don’t sell AI as fashion — if the process doesn’t need AI, we don’t add it. We charge for automations that work, not for technological adjectives.

  • ×

    Nor automate what we can’t measure — without baseline of hours, cost or errors before touching anything, there’s no pilot. Faith doesn’t pay salaries.

  • ×

    Nor subcontract to juniors — AI flows, prompts, scoring and CRM integration are designed by a senior. If needed, AI supports for speed. Never the other way around.

  • ×

    Nor lock you in — month to month, full access to your accounts. You stay because it works.

  • ×

    Nor invent case studies — real accounts with real data before you sign anything.

  • ×

    Nor generate content without human review — AI speeds, senior decides. We never publish without editorial judgment on top.

Real numbers

What applied AI moves, measured.

−68%

Operational time on repetitive flows

lead enrichment, assignment and reporting. Same people, more pipeline managed and fewer manual errors.

4.3×

Content production speed

AI pipelines for briefs, drafts and variants with senior review. More posts and landings per week, same brand voice.

+31%

Lead scoring accuracy

models trained on real CRM history vs rule-based scoring. Fewer hot leads forgotten, fewer cold ones swamping the rep.

Average figures from AI deployments in B2B accounts managed by Esconzeta in 2025-2026. Results depend on data quality, digital maturity and operation volume.

Sectors

Is this for my business?.

It depends on what you want to build.

We work with businesses that no longer want to improvise. That seek direction, not just execution.

EDP
Eleia Energía
Flame Analytics
Fotocasa
Santillana
Viacore
ULMA
Esnova
Ferrovial
Helvetia
ITC
Neodoc

A shared goal:
making every decision count.

Frequently asked questions

What our clients ask us.

Does AI replace my marketing team?

No. It replaces tasks, not people. AI eats repetitive, low-judgment work: briefs, first drafts, reporting, scoring. What your team does well (strategic judgment, client relationship, investment decisions, contextual creativity) AI doesn’t do yet. If your agency sells AI as human substitute, be suspicious.

Where do we start if we’ve never automated?

By the process burning the most hours and whose result you can measure. In practice usually: lead capture and enrichment, sales rep assignment, follow-up and leadership reporting. In 60 days we free 15-40 weekly hours with basic flows. Don’t start with a chatbot if your pipeline is not yet ordered.

Which tools: n8n, Make or Zapier?

All three have a place. Zapier for simple flows with standard cloud tools. Make when there’s serious conditional logic and high volume with contained cost. n8n self-hosted when you want full data control and strict GDPR. The decision is not religious: depends on stack, volume and team. We decide after mapping, not before.

Does AI content rank on Google?

AI content without human review doesn’t rank: Google detects it. AI content with solid brief, own data, senior editorial judgment and final review ranks exactly like 100% human. The key isn’t who writes the first draft: it’s who adds the edge, real examples and judgment before publishing.

Is AI worth it for B2B with limited data?

Depends on use case. For flow automation and assisted content generation, yes: no own history needed. For predictive analysis you need at least 12-18 months of CRM data and 300-500 closed deals. If you don’t have that history, the first step isn’t the model: it’s ordering the data.

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