For teams scaling with complexity

Turn Fragmented Data IntoTrusted Decisions

We help leadership teams align around shared metrics, governed models, and AI-ready data access so teams can answer important questions faster.

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Where Growing Teams Get Stuck

You do not need more dashboards. You need a shared decision layer that helps teams answer operational and commercial questions without metric debates, reporting bottlenecks, or fragile logic.

Metrics change depending on who answers

Finance, operations, growth, and leadership often rely on different definitions, which turns roadmap conversations into debates about whose number is right.

Important questions wait in analyst queues

When reliable answers depend on ad hoc pulls, teams move slower, lose momentum, and make prioritization calls with partial context.

Reporting gets rebuilt over and over

Without shared models and documented logic, every new dashboard or one-off analysis recreates the same business rules in a slightly different way.

AI gets added before the foundation is ready

Natural-language analytics and internal copilots only help when the underlying data, governance, and ownership model are already trustworthy.

Outcomes & Proof

Featured proof

Takenos: building a decision-ready data foundation in roughly two months

We helped Takenos unify behavioral, operational, and business data into a governed analytics layer that multiple teams could use. The point was not just to install tools. It was to reduce metric ambiguity and give the company a more reliable basis for decision-making.

The case study also shows the delivery model behind the work: visible weekly cycles, structured workshops, and a clean handoff so the internal team could keep extending dbt with confidence.

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Speed to value

From zero to a decision-ready analytics foundation

Takenos stood up its core modern data architecture in roughly two months without turning the work into a black-box implementation.

Enablement

Workshops that made handoff real

The engagement included structured workshops so the internal team could understand the architecture, modeling approach, and dbt workflow after delivery.

Alignment

Shared analytics layer across teams

Finance, operations, growth, and leadership moved toward common definitions instead of each function maintaining its own partial version of the truth.

Access

AI assistant on top of governed logic

Stakeholders gained a plain-language way to access trusted information without bypassing the warehouse models and governance underneath.

Trusted by teams building with complexity

We have partnered with fintech and digital teams that need reliable infrastructure, aligned metrics, and stronger decision support as they scale.

How We Help Teams Scale

We are not just implementing a stack. We help teams build the shared data layer, operating model, and access patterns that improve the speed and quality of decision-making.

Build a Trusted Decision Foundation

We connect behavioral, operational, and commercial data into a governed analytics layer your team can actually rely on for decisions.

Create Shared Metrics Across Teams

We model the definitions that keep finance, operations, growth, and leadership aligned instead of reconciling numbers in every meeting.

Enable Faster Answers With AI-Ready Access

From governed warehouses to natural-language analytics experiences, we make trustworthy information easier to access without bypassing the underlying logic.

Deliver With Your Team, Then Hand Off Cleanly

We work in visible weekly cycles, document the modeling layer, and help internal teams take ownership instead of inheriting a black box.

How We Work

Senior teams usually need more than implementation capacity. They need a delivery model that keeps the work visible, aligns people around shared logic, and leaves the company stronger after the engagement.

Align on the Questions and Definitions

We start with the business questions that matter most, then map the shared metrics and source systems behind them.

Deliver in Visible Weekly Cycles

Instead of disappearing into a long implementation, we keep progress collaborative, reviewable, and tied to the teams who will use the outcome.

Model for Trust, Reuse, and AI Readiness

We build governed transformation layers, documentation, and access patterns that make dashboards, analysis, and AI workflows safer to scale.

Transfer Ownership to the Internal Team

Workshops, code reviews, and a maintainable dbt workflow help your team extend the foundation after handoff instead of depending on us forever.

Who You’ll Work With

A small senior team that stays close to the work. We combine commercial context with deep data engineering execution so the output is useful to both decision-makers and implementers.

Marco

Co-Founder & Data Engineer

Works with data and business leaders on governed metrics, scalable analytics foundations, and AI-ready access patterns for transaction-heavy businesses.

Manuel

Co-Founder & Data Engineer

Leads hands-on delivery across data platforms, dbt workflows, and cloud architecture with a strong focus on maintainability and team ownership.

Juan Pablo

Data & AI Engineer

Builds the tooling, integrations, and AI-enabled workflows that make modern analytics systems more reusable, accessible, and production-ready.

Google Cloud Partner

Technical services partner

As a Google Cloud Partner, we help teams design and operate data foundations on infrastructure that can scale with organizational complexity. That matters when analytics, AI workflows, and internal decision systems need to be reliable from day one.

Bring Us In When Important Questions Outgrow Ad Hoc Reporting

If your team needs aligned metrics, faster answers, or an AI-ready analytics foundation, we can help you scope the right next step.

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Insights for Decision-Makers

Case studies and practical perspectives on shared metrics, AI adoption, and delivery models that make analytics more useful across teams.

Case StudyShared MetricsFintech

Takenos Case Study: A Decision-Ready Data Foundation in 2 Months

How we aligned finance, operations, growth, and leadership around shared metrics and a governed analytics layer in roughly two months.

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AITeam EnablementAgents

Why Teams Should Start Building and Sharing AI Agents Now

A practical take on how teams can operationalize AI around real workflows once the right data foundations are in place.

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EngineeringData PlatformsDelivery

From Software to Data: Building the Tools We Need

An inside look at how we build reusable data tooling and delivery systems instead of reinventing the plumbing on every engagement.

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Open Source That Supports Delivery

We build and share reusable tools because strong delivery depends on repeatable systems, not reinventing the plumbing on every engagement.

PythonETLBlockchain

tap-dune

A Tap adapter for Dune Analytics, enabling seamless data extraction from on-chain data queries.

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PythonFirestoreETL

tap-firestore

Google Cloud Firestore tap adapter for reliable data ingestion into your modern data stack.

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PythonIdentityETL

tap-persona

Identity verification data integration for building trusted user onboarding flows.

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PythonDatabaseETL

tap-turso

Turso database tap adapter for edge computing and distributed database scenarios.

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TypeScriptAITemplates

template-claude-plugins

A template repository for building Claude AI plugins with best practices and scaffolding.

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