Find the right starting point.
We listen, look at your current setup, and identify the problem worth solving first.
A focused planDATA & AI CONSULTING FOR SMALL BUSINESSES
Reliable data.
Practical AI.
Within reach.
Build a stronger data foundation. Connect the AI tools you already use to your business. Make progress that fits your budget.
Start small Move fast Keep costs under control
CONNECTING THE DOTS01 — 03
YOUR BUSINESS
YOUR AI TOOLS
Less busywork. More possibility.Business context, connected to everyday AI.
Thoughtful integration. Useful outcomes.
Hands-on experience.
A dependable foundation.
aws❄ snowflake✳ dbt✣ AirflowPython
WHAT WE DO
The right support.
Where it matters most.
From getting your data in order to putting AI to work, we turn complex challenges into practical next steps.
01 /
MAKE MORE OF THE AI YOU ALREADY USEAI tools. Your business data.
Connect the AI tools your team already uses to the knowledge and systems that make your business run.
Connect your business
02 /
A stronger data foundation.
Build a dependable cloud data platform that fits your workload today and gives you room to grow.
Explore service
03 /
Pipelines that keep moving.
Replace fragile workflows with reliable pipelines, clear data models, and checks that catch problems early.
Explore service
04 /
More value. Less overhead.
Find what is slowing you down or driving up your cloud bill, then make targeted improvements.
Explore service
A MORE USEFUL WORKDAY ILLUSTRATIVE WORKFLOW
YOU
What’s our onboarding process for a new client?
Here’s the process from your team’s onboarding guide:
- Confirm the scope and assign an owner.
- Collect the client’s setup information.
- Schedule the kickoff and share next steps.
Your knowledge. Easier to find and use.
AI THAT KNOWS YOUR CONTEXT
Your tools are smart.
Make them
business-smart.
Your documents, knowledge, and business systems hold valuable context. We help connect it to tools like ChatGPT, Claude, and Gemini through supported integrations.
Start with one useful workflow. Reduce repetitive work. Give your team more time for what matters.
Put your existing AI to workHOW WE WORK
Start small.
Build with purpose.
Clear scope, sensible tools, and a useful outcome at every step. Your budget is part of the brief from day one.
Build something useful.
We implement a focused solution, using your existing tools wherever they make sense.
A working solutionMake it yours.
We test, document, and walk your team through it so you can operate it with confidence.
A clear handoffTHE LEAD BEHIND THE WORK
Hi, I’m Randy.
I lead the team.
I’m the lead engineer and project lead at South Bay Data, with experience spanning cloud data platforms, analytics infrastructure, and AI applications.
My background includes building large-scale lakehouses, modernizing legacy pipelines, and developing retrieval and natural-language data tools. I stay closely involved from discovery through delivery and bring in the right engineering experience for each project.
Good technology should make your business easier to run.
Let’s talk about your projectA SMALL, EXPERIENCED TEAM
Specialists for the
work at hand.
Randy leads every engagement, supported by engineers with complementary experience across analytics, finance, data platforms, and enterprise warehousing.
ENGINEER 02
Senior Business Intelligence Engineer
AI data, analysis & visualization
Brings senior BIE experience from Amazon, with a focus on data analysis, clear visualization, and organizing business context and semantic data for AI systems.
ENGINEER 03
Data Engineer
Finance data & lean platforms
Brings experience from a large entertainment company, building finance data pipelines and practical data infrastructure for small, fast-moving teams.
ENGINEER 04
Data Engineer
Enterprise data warehousing
Brings experience from a large insurance company, with deep knowledge of traditional data warehouses, ETL, dimensional modeling, and warehouse modernization projects.
EXPERIENCE THAT TRANSFERS
Big-system thinking.
Small-business focus.
Selected areas from Randy’s engineering background.
Data platforms at scale
Architecture and implementation of petabyte-scale lakehouses on AWS.
Modernization in practice
Migration of legacy data workflows to Airflow and dbt, with quality checks and automated deployments.
AI connected to real data
Retrieval pipelines, vector search, and natural-language access to business data.
A FEW GOOD QUESTIONS
Before we get started.
Can we start with a small budget?+
Yes. We can begin with one workflow, a focused assessment, or a specific bottleneck. We’ll agree on the scope and budget before implementation, then expand only when there’s a clear reason.
Do we need to build our own AI product?+
Often, an integration with a tool your team already uses is a practical starting point. We assess your requirements and the available integrations before recommending custom development.
Will this work with our existing tools?+
We start by reviewing your tools, subscriptions, and data sources. Where supported, we use connectors or APIs to bring them together. We explain any limitations and additional costs before building.
How do you handle access to company data?+
We define which data the workflow needs and who should be able to access it. Integrations are designed around those permissions, with attention to what information is shared with each AI service.
What happens after the project?+
You receive documentation and a walkthrough of the solution. We discuss maintenance responsibilities and any ongoing support needs as part of the scope.