A common language
Shared metrics, entities, events, taxonomies and accountability across teams.
03 · Making brands visible to machines
Data, content and intelligence systems built for better decisions.
We organize data and knowledge, connect analytics and martech, and build content systems prepared for search, LLMs, automation and emerging interfaces.
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A useful data and intelligence strategy connects sources, definitions, quality, access and decisions. For marketing and growth, it also includes structured content, taxonomy, measurement and signals that help people and machines find, interpret and use what the company knows.
Fragmented data, inconsistent metrics and unstructured content weaken every decision and AI application built on top. Before adding more tools, the system needs to become legible, trustworthy and actionable.
What changes
Value that shows up in operations.
Actionable intelligence
Data and analysis connected to questions, decisions, alerts and real workflows.
Discoverable content
Editorial and technical architecture prepared for search, generative answers and reuse.
How we help
From decision to a working system.
Data strategy and architecture
Sources, entities, events, integrations, quality, access, governance and roadmap.
Analytics and measurement
Metric frameworks, instrumentation, attribution, dashboards and decision cycles.
Martech and integration
Stack assessment, data design, automation and connections across platforms.
Knowledge systems and RAG
Content, metadata, permission, retrieval and freshness for people and agents.
SEO, GEO and content architecture
Pages, entities, links, structured data and editorial systems for discovery.
AI-enabled content operations
Workflows to research, create, review, localize, publish and measure quality content.
Where it applies
Problems this work is built to solve.
- Unify marketing, media, CRM, commerce and product data and definitions.
- Prepare enterprise knowledge for copilots, agents and internal search.
- Build a multilingual content operation around SEO and GEO.
- Turn passive dashboards into alerts, recommendations and operating decisions.
How we make
A short path to real evidence.
Map
Identify decisions, sources, users, definitions, quality and the highest-value gaps.
Structure
Design models, taxonomy, events, integration, governance and content architecture.
Activate
Implement the first end-to-end data, intelligence or publishing flow.
Measure and learn
Track usage, trust, discovery and impact to improve the system.
Frequently asked questions
Before we begin.
What is the difference between a data strategy and a BI project?+
BI is one part of the system. Data strategy starts with decisions, then defines sources, quality, models, access, governance, integration and operations. A dashboard creates value only when it is connected to action.
What is GEO and how does it relate to SEO?+
SEO improves discovery in search engines. GEO structures content, authority and evidence to improve the likelihood that a brand is understood and cited in generative answers. Both depend on strong technical and editorial foundations.
Does MAKINAI implement martech and analytics platforms?+
Yes. Work can include assessment, architecture, selection, instrumentation, integrations, dashboards and automation. Recommendations begin with the operating problem rather than a preferred vendor.
Must all data be centralized before a company can use AI?+
No. A company can begin with one bounded domain and use case. The important requirement is clarity on source, quality, permission, freshness and usage limits.
What we make
Capabilities designed to connect.
MAKINAI · Making brands visible to machines