Business sponsors
Agree the intended outcome, users, priorities and how the work will be accepted.
YOUR GOOGLE CLOUD TEAM
Google Cloud AI services
Identify useful AI opportunities, assess data readiness and build solutions with evaluation, governance and a practical path to production.
Discuss your data platform ↗Data, analytics and AI guidance
Explore the capabilities, methods and practical resources for your project. Scope, licensing, timing and support are agreed with your Cloudypedia team.
AI Solutions
SMB friendly AI and ML services
What is Google Cloud AI Platform Consulting Services?
This service utilizes Google Cloud AI Platform tools and infrastructure such as Auto ML and Google APIs to build an end to end an AI enhanced applications. This consulting service also helps you explore your data to identify meaningful use cases, validates assumptions and helps integrate to production.
Benefits of Google Cloud AI Platform
Leadership: Google created TensorFlow in 2014 and open source .
Cost effectiveness: Flexible on demand compute options that are up to 70% cheaper than competition
Prepackaged yet powerful AI solutions for Enterprises new on the AI path with very limited resources
Cloud AutoML helps businesses with limited ML expertise to start building their own high-quality custom models
For advanced enterprises on AI journey who have data scientists and ML experts inhouse to train ML models using TensorFlow, Cloud TPUs, GPUs and ML engine
Benefits of Cloudypedia Services
Cloud data engineering certified team
In house data scientists ready to help SMB teams
Fast and proven use-case validation methodology
Domain expertise in Financial Services , Retail, Manufacturing, Healthcare, Sales, Marketing
Google Cloud AI platform meets you where you are
Google Cloud AI Platform Projects Process
Cloud AI Explore
Cloud Explore: This service helps you understand machine learning (ML) concepts and identify and qualify potential business problems that can be addressed using ML. Ideal for determining if ML is right for your business and which use cases are realistic and achievable.
Objectives
Gain new competitive advantages with ML
Identify potential ML use cases
Address targeted business problems
Survey the foundation for ML potential
Activities and Deliverables
ML overview session
Use case ideation workshop
High-level data qualification
Analysis and recommendations
Cloud AI Validate
Cloud AI validate service helps you take the use case identified in Cloud Explore from theoretical to practical by developing an ML model. This model will prove the value of the use case and its ML solution to stakeholders prior to investing more in the next phase of build out.
Implements steps 2–7 in the ML life-cycle
Delivers a minimum viable ML model or feasibility study
Delivers 12 days of work effort in a 6-weeks calendar window
Engagement activities
Develop an ML solution model
Perform exploratory data analysis
Explore the right set of features to include
Present results of the model that shows its business value
Deliverables
Data exploration
Data pipeline and feature engineering
Build and iterate ML model
Present results to stakeholders
In Scope of Cloud AI Validate
Data exploration
Algorithm selection
Data pipeline
Feature engineering
Development of initial ML model
Iteration to improve performance of ML model
Out of scope of Cloud AI Validate
Building a complete data pipeline
Deploying the model into production
Converting the model into an API
Start exploring your AI project email: ai@cloudypedia.com
Make the next conversation useful.
Bring the business outcome, current environment and constraints. We can then define a suitable assessment, implementation or ongoing service.
Technical teams
Review architecture, integrations, data access, security and operational ownership.
Procurement teams
Confirm scope, contracting entity, licensing route, commercial terms and support responsibilities in the proposal.
What shapes your proposal?
Workload complexity, dependencies, data location, delivery responsibilities and operating needs determine scope and timing. Licensing, billing currency, taxes, payment terms and support coverage are confirmed for the relevant market and agreement.
