About
Use Cases
Services
Why FDO?
Let's Talk
About Us

FDO is a gig economy deep skill network of data and AI professionals for fractional services with coordination and accountability.

The new ways of working post-pandemic have made it possible for FDO to tap into top talent. FDO’s top data and AI talent is recruited via referrals. You can expect baseline productivity of at least 2x. Get value from your data at a fraction of the cost in a fraction of the time. With FDO you only pay for the skills you need for the time you need - without having to hire, fire or pay salary and benefits.

Why now? AI fueled by data is driving the fastest and biggest productivity growth in history. This is expected to happen in the next 3 years and drive productive growth of at least 50%. For comparison, the advent of computers and the internet drove productivity growth by 10% and took 20 years. Institutions and companies that don’t leverage data and AI can expect to be left behind.

Anto Thomas
Managing Partner / Co-founder
Joshua Thomas
AI Product Manager
Our Services
Data Strategy
The development of a comprehensive plan for how an organization collects, manages, and utilizes data to achieve its business objectives.
Data Products
The development and delivery of data-driven solutions and services that enable business decision-making and improve outcomes.
Data Platform
The underlying technology infrastructure that supports the storage, processing, and analysis of an organization's data.
DataOps
The process of designing, building, and managing data pipelines and workflows in order to streamline data operations and make data more accessible and useful
Data Engineering
The process of designing, building, and managing the systems and infrastructure that enable organizations to collect, store, and process large volumes of data.
DS/ML/AI
The fields of Data Science, Machine Learning, and Artificial Intelligence that utilize data to build models and algorithms that enable predictive and prescriptive analytics.
Data Architecture
The process of designing and defining the overall structure and organization of an organization's data assets, including data models, schemas, and metadata.
Data Modeling
The process of creating abstract representations of data and defining relationships between different data entities, often using diagrams and other visualizations.
Data Analysis
The process of using statistical and other analytical methods to extract insights and meaning from data.
Operational Analytics
The use of data and analytics to optimize business operations and improve efficiency and effectiveness.
Data Governance
The development and implementation of policies and procedures to ensure that data is managed and used in a consistent, secure, and compliant manner.
Metrics
Quantitative measures that are used to evaluate and track performance and progress towards business goals.
Data Monetization
The process of generating revenue from data assets, typically through the development of data-driven products and services or through the sale of data to third parties.
Data SM/PM
The fields of Data Management and Project Management that focus on the effective management and implementation of data projects and initiatives.
Data Privacy
The protection of personal and sensitive data from unauthorized access, use, and disclosure, typically through the implementation of security and privacy controls and practices.
Data Value
The measurement and evaluation of the impact and business value of data assets.
Actionable Dashboards
Dashboards that provide insights and recommendations that enable business decision-making and action-taking.
Data APIs
Application Programming Interfaces that enable applications and systems to access and interact with data assets.
Data Streaming
The process of collecting and processing real-time data as it is generated, often used for real-time analytics and decision-making.
Dashboards
A visual representation of data that provides a summary of key metrics and indicators, typically presented in a single view or dashboard.
Data Literacy
The ability to read, understand, and work with data effectively, typically through the development of data skills and competencies.
Use Cases

You have a data platform, but it’s gotten dated and has not evolved to take advantage of modern tools and technologies like Cloud, Machine Learning, Artificial Intelligence, ELT, Lake Houses, Reverse ETL’s, Metric Layers, Notebooks, Collaborative development, Copiloted Development etc. FDO can help with strategies to modernize and bring in Fractional Data and AI teams to execute and deploy a modern stack to keep your competitive edge.

Why FDO?

01

Gig Economy Efficiencies

An effective data and AI team requires several deep skill sets from strategy, engineering, and cloud to DevOps and governance. It can be prohibitively expensive to hire a full team of employees or consultants, let alone retain and fully utilize them. FDO leverages the metered efficiencies of a gig workforce to solve this by bringing in the deep skills you need when you need them and only for the time you need them for.

02

Deep Data
and AI Skills

FDO provides access to specialized expertise that is difficult or costly to find and develop in-house. This includes experts on all the public cloud data services (AWS, Azure, and Google), leading data platforms like Snowflake and Databricks, streaming platforms like Kafka, and AI models and apis like OpenAI/GPT, Claude, Bard, LLaMA, Gemini, and other open source software.

03

Coordination
& Accountability

The magic with a deep-skill gig team happens when there is great coordination and accountability. This is a key differentiator with FDO, where skilled gig product and project managers coordinate the gig team working on your project to make the magic happen.

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