Make Better Use of Your Data.
Find Practical Opportunities for AI.
Data Novera helps growing businesses understand their data, strengthen their data foundation, and explore practical ways to use AI.
- 01Understand your data
- 02Find the opportunities
- 03Test what works
- 04Build what matters
Does Your Data Make Your Business Harder to Run?
Many businesses have valuable data, but it isn't always connected, easy to trust, or easy to use.
Your data lives in too many places
POS, accounting, CRM, the online store, and a few spreadsheets nobody wants to touch.
Reports still require too much manual work
Someone exports, copies, and pastes every week just to answer the same questions.
Different teams see different numbers
Sales and finance both have a revenue figure. They rarely match.
Important information is difficult to find
It exists somewhere, but only one or two people know where to look.
You want to use AI, but aren't sure where to start
There are a lot of tools and a lot of noise. It's hard to tell what fits.
Your team doesn't have time for data projects
Everyone is busy running the business. Data work keeps getting pushed back.
Is Your Business Ready for AI?
AI starts with more than choosing a model or buying another tool. It starts with understanding your data, your processes, and the problems you want to solve.
- 1First, the foundationData
What you have, where it lives, and whether you can trust it
- 2Governance
Who owns it, what it means, and who can use it
- 3Architecture
How it's stored, connected, and kept up to date
- 4Then, opportunityAI Opportunities
Where AI could genuinely help, and where it won't
- 5Prototype
A small, working test of one good idea
- 6Scale
Turn what works into something the business relies on
We help businesses understand where they are today, identify the gaps, and decide what is worth doing next.
More on AI readinessData & AI Readiness Assessment
A focused way to understand where your business stands today and what should happen next.
- Step 1
Understand
Review the systems, data sources, processes, and current challenges.
- Step 2
Assess
Look at data quality, architecture, integration, governance, accessibility, and AI readiness.
- Step 3
Identify
Find realistic opportunities where better data, analytics, automation, or AI could help.
- Step 4
Prioritize
Create a practical roadmap showing what to address first and what can wait.
What you receive
- Current-state overview
- Data and system inventory
- Key data gaps
- Architecture observations
- AI opportunity areas
- Prioritized recommendations
- Suggested next steps
A clear picture of where you are and a practical plan for what to do next.
Start Small. Learn. Then Build.
You don't need a large upfront technology project. Start with a real problem, test something small, and only build further when it makes sense.
- 01
Understand
Start with the business problem and understand how data is being used today.
- 02
Assess
Find the gaps that are getting in the way.
- 03
Prototype
Test an idea with something small and useful.
- 04
Build
If the idea works, turn it into a solution that can grow.
Organized around what your business needs
Most work touches more than one of these. We start wherever the real problem is.
Data Architecture
Modern cloud data platforms designed around how the business actually works.
Data Integration
Connect information from systems such as POS, ERP, CRM, e-commerce platforms, APIs, databases, and files.
Data Governance
Improve data quality, ownership, metadata, lineage, and trust.
Analytics
Create a more consistent foundation for reporting and business insights.
AI Readiness
Prepare data and processes for practical AI use cases.
AI Applications & Agents
Explore assistants, agents, and other AI applications built around useful business information.
Most of our work is on Azure or AWS, with Databricks, Snowflake, SQL, and Python, and current language models where they fit.
More on what we doPractical projects and reference architectures
A client project is real work for a paying client. A reference architecture shows how we would approach a common problem. It isn't client work, and we label it that way.
Why Data Novera?
A small practice with a lot of hands-on experience behind it. Here’s what that means when you work with us.
- Experience
- Built on more than 20 years of experience working with data, software, and technology.
- Practical Thinking
- Start with the problem, understand the data, and choose technology that makes sense.
- Data + AI
- Good AI depends on good data. We look at both.
- Direct Collaboration
- Work directly with experienced technical leadership rather than being passed between layers of an organization.
Want to talk through a data or AI problem?
Bring it as it is. We'll help you work out a sensible place to start.