Recurring Collection
Each report starts by exporting, copying and correcting data that was already prepared the previous month.
KarminaAI StudioAgents · Services · Training
SERVICES · DATA AND DECISION
Connected data. Decisions in context.
We convert scattered sources, contradictory metrics and recurring reports into a data system that explains what happens, what needs attention and who needs to decide.
Sources · Definitions · Dashboards · Decisions
AnalyticsSourcesDictionaryQualityReadingDecision
SERVICES
A selection of routes. The same knowledge base, criteria and people.
01
LLM StrategyAdoption, Governance and Roadmap
Explore ↗02GEOSearch engine visibility and responses from AI
Explore ↗03AnalyticsConnected data to decide
Current ↗04Business Plan with AIBudget, workflows, return and roadmap
Explore ↗05Social ListeningListen, Context and Recurring Consulting
Explore ↗06ATCPeople, Knowledge and AI
Explore ↗07AI master planManagement, Governance and Adoption
Explore ↗08Creative FlowRecurrent creativity with integrated AI
Explore ↗09Social Media OSShared social strategy and operation
Explore ↗10Brand PlaybookApplicable brand and knowledge
Explore ↗11OpenAI AdsPerformance conversational and measurement
Explore ↗12AI campaigns and videoConcept, production and activation
Explore ↗IN A SCREEN
Analytics is the service that connects sources, definitions, controls and visualization so that a dashboard ceases to be a showcase of metrics and becomes a decision tool.
WHAT THE SERVICE IS
The problem is not usually the lack of data. I don’t know what version the business is.
Campaigns, networks, web, CRM, sales, projects and budgets can describe different realities. When each team calculates periods and indicators in its own way, automating the reporting accelerates the contradiction.
The main work happens before the dashboard: agreeing definitions, documenting transformations, assigning responsibility and deciding what change deserves an alert or a conversation.
START POINT
When the reporting takes longer than it helps to decide
If you recognize yourself in more than one of these signals, the first step is not to add more technology. It is to build a shared reading of the problem.
Metrics with the same name
Two platforms or teams use the same label, but not the same calculation, period or scope.
Dashboards without reading
There are many charts and little context about what has changed, why it might have happened and what needs to be reviewed.
Warnings that create noise
Notices have no proportional thresholds, accountability, or a defined action after notification.
Data without trace
A figure has been transformed, estimated or corrected, but the system does not let you know where it comes from.
Learning that doesn’t come back
The decisions of the month do not update definitions, hypotheses, objectives or the reading of the next cycle.
COMPANY BRAIN · ADAPTED TO THE SERVICE
The data is the dynamic layer of Company Brain.
A useful corporate memory doesn’t just hold documents. It also knows what data change, how often, who validates them and what decision they must feed.
Operational Sources
Platforms, CRM, web, sales, projects, budgets and other systems necessary for the question.
→Shared Dictionary
Definition, formula, period, unit, scope, frequency, owner and limitations of each indicator.
→Quality and traceability
Duplicates, absences, estimates, transformations and data still pending validation.
→Dashboards, alerts and reports
Each view adapts to a decision and shows context, not just accumulation of metrics.
→Documented decisions
The system preserves what was interpreted, what was done and what needs to be compared to the next cycle.
Technology contrasts. Knowledge is oriented. People decide.
BEFORE YOU CLOSE ABAST
You do not need to arrive with a defined solution.
We can review the challenge, starting point and priorities in a free video call. Putting order before writing the scope usually saves time and budget.
Video call · free · no obligationBook a free video call ↗A short conversation to understand your starting point and bring clarity.
ABAST MODULAR
An analytics system, not just a dashboard
We can start with a single recurring decision and the minimal sources to explain it. When the first reading is reliable, the system grows by blocks.
Questions, Reports and Sources
We identify which decisions should be fed, who uses each report and where frictions or contradictions occur.
- Inventory of sources and reports
- People, uses and cadences
- Empty and duplicated
Dictionary of Metrics
We agree what each indicator means and document formula, period, scope, quality, frequency and responsible.
- Shared definitions
- Rules of Transformation
- States of Validation
Proportional data layer
We connect only the necessary sources and maintain separation, permissions and tracing according to the sensitivity of the information.
- Integrations and Updates
- Minimum permits
- History and Incidents
Dashboards and useful alerts
We design views for a decision, with hierarchy, context, comparison and notices that indicate what needs to be reviewed.
- Executive and operational reading
- Threshold and responsible
- Access from different devices
Narrative, Hypothesis and Learning
The AI can summarize patterns, compare periods and prepare hypotheses, always showing limits and without converting correlations into causes.
- Reviewable summaries
- Anomalies and Questions
- Trace of decisions
HOW WE WORK
Start with a decision, not all data
We select a recurring question, reconstruct its trace and check the first version against previous reports before expanding channels or automations.
Scroll to follow the route →01. Define the decision
We agree on what the team needs to understand, how often, and what they will do when the signal changes.
· brief decision output02. Locate the sources
We identify systems, fields, periods, accesses, exports, owners and limitations.
Exit · data map03. Create the dictionary
We resolve discrepancies and document calculations, transformations, frequency, quality and accountability.
· Output Ruled Metrics04. Build the minimum layer
We automate the necessary collection with proportional permissions and sufficient registrations.
Exit · first version05. Validate the reading
Contrast the result with previous reports and with people who know the context.
Output · QA and settings06. Activate the cycle
We define alerts, reports, responsibilities and how each decision will update the system.
Exit · recurring operationWHAT THE ORGANIZATION CAN RECEIVE
Data with definition, context and possible action
- ✓Map of recurring questions and decisions
- ✓Inventory of sources, reports and dependencies
- ✓Dictionary of Metrics and Dimensions
- ✓Quality rules, transformation and validation
- ✓Integration architecture and permissions
- ✓Dashboard executive and/or operational
- ✓Alert with threshold, responsible and action
- ✓Reviewable periodic narrative report
- ✓Record of incidents, hypotheses and decisions
- ✓Maintenance and responsible manual
FORMATS
Three Project Scales
Not all organizations need to get to the same place. We define a phase that leaves a useful decision or asset for itself.
Audit and Dictionary
To understand the sources, resolve discrepancies and leave a common foundation before viewing.
Result · map and definitionsreporting System
To connect priority sources with views, controls, alerts and a recurring reading.
Result · dashboard validatedAugmented Analytics
To add comparisons, summaries, hypotheses and learning with AI on an already governed basis.
Result · decision cycleKarmina, the agency behind the Studio
Why Karmina?
Behind Karmina AI Studio there is an agency with track record, team, scale and applied experience in real organizations.
Karmina · AI Studio · Criterio · Dunder Mifflin · Utopiq · Smart Team
+€119mIn advertising investment for clientsAds Platforms
Partners
MetaGoogle Ads
TikTok
Pinterest
BarcelonaMadrid
Buenos AiresOur offices · Meet the team ↗
+50 KCommunity
B CorpCertified companyIF YOU ALREADY HAVE MATERIAL
Do you already have a brief? Send us.
It can be a finished document, a few notes or an email with context. We will read it before proposing a conversation or a first step.
Success stories · From 2015
From consulting to projects that come into operation.
01City Council
Terrassa
Terrassa
Public administration · LLM Strategy
Terrassa City Council
View case study ↗02
Public infrastructure · Social Media OS + Agents
Aena
View case study ↗03
Nonprofits · Training + adoption AI
Associació Alba
View case study ↗04
Consumo · Social Publisher
De’Longhi
View case study ↗05
Editorial · Knowledge Guide
Salvat
View case study ↗06
Public administration · Meeting Notes
Diputació de Barcelona
View case study ↗07
Food and drinks · Benchmark Scout
D.O. Cava
View case study ↗08
Restoration · WhatsApp Desk
UDON
View case study ↗09
Beauty · Landing Builder
Labeau Organic
View case study ↗10
Food · Dashboard Builder
Damel Group
View case study ↗11
Retail and Fashion · Market Scout
Zara
View case study ↗Move horizontally to see more cases
The team
A connected service with strategy, knowledge, data, creativity and implementation
Arnau Sanz
Agentic Strategy & AI Transformation Lead
Ignasi Llorente
AI Partnerships & Business Director
Martina Díaz
AI Finance & Business Intelligence Director
Daniel Mallén
AI Operations & Workflow Lead
Eva Trigo
Generative Creative Director
Ariadna Miranda
AI Administration & Knowledge Operations Lead
Claudia Gonzalez
AI Client Success Manager
Jonan Basterra
AI Social Strategy Director
Laura Sabio
Agentic Social Media Lead
Agustina Córdoba
Content AI Specialist
Alba Gómez
Social Listening Specialist
Paola Cudeiro
AI Client Success Specialist
Roger López
AI Project & Workflow Specialist
Mar Berzal
AI Content Strategy Lead
Andrea Gallego
Community Intelligence Specialist
Candela de la Fuente
Content AI Specialist
Blanca Gómez
AI Community Operations Specialist
Cintia Armajach
Content AI SpecialistFREQUENTLY ASKED QUESTIONS
Before we start.
01Do you need to replace the tools we already use?+
No. Most projects are based on existing sheets, platforms and systems. We decide what can be preserved, connected or simplified before proposing a new layer.
02Can you connect any source?+
We evaluate it according to access, quality, safety, need and maintenance cost. Connecting a source is not a goal in itself; it must help answer a specific question.
03What does AI bring to reporting?+
It can compare periods, detect changes, summarize patterns, and prepare hypotheses or first drafts. People continue to validate context, causes, decisions, and exceptions.
04How do you handle personal or sensitive data?+
We apply minimum purpose and permissions. If a data is not necessary for the decision, it should not enter the analytical or generative layer. The specific scope is validated with those responsible for the organization.
05Can we start with a single report?+
Yeah. It is often the best option: select a recurring decision, build a reliable first version and expand only when the team already uses it and can maintain it.
Let's talk about Analytics
What recurring decision needs a more reliable reading today?
You don’t have to come up with a defined architecture. Tell us which report, dashboard or data process concentrates more time, contradictions or doubts, and we will delimit the minimum sources to start.
hello@karmina.ai