01 · Know what to build
Data and Analytics
Getting your data into a state where it can be trusted, then turning it into reporting people actually read. Often the necessary first step before any AI project is worth starting.
Why people ask for this
- Numbers that disagree depending on who produced them
- Reporting rebuilt by hand every month and out of date by the time it is read
- No agreed definition of a customer, a lead or a sale
- An AI project that cannot start because the data is not trustworthy
What we build
A scope is assembled from these based on what your situation actually needs — not all of it, and rarely in this order.
Foundations
- Data collection and cleaning
- Data transformation and migration
- Database and schema design
- Data pipeline development
- Data quality audits and reconciliation
Reporting
- KPI and executive dashboards
- Sales, marketing and operations reporting
- Financial and support dashboards
- Automated recurring reports
- Analytics tracking setup
Analysis
- Customer segmentation
- Funnel and lead analysis
- Churn analysis
- Forecasting
- Natural-language questions over your data
Often combined with
AI Automation
We map the tasks your team repeats every week, then build systems that carry them out consistently — following your rules, without needing a person to move the work along.
Learn more →MCP and Integrations
Most AI projects fail on plumbing, not intelligence. We connect your CRM, calendar, database, storage and finance tools — including through MCP, an open standard for giving AI controlled access to real systems.
Learn more →AI Websites and Web Applications
Websites, portals and internal tools built to be fast, accessible and maintainable. Where AI genuinely helps — search, drafting, triage — we build it in. Where it does not, we leave it out.
Learn more →Let’s talk about data and analytics.
Describe the process you have in mind. We will tell you plainly whether this is the right fit, what it would involve, and when it would not be worth doing.
hello@aigenflow.net