Hands-on help to make your data team AI-capable
Grounded Analytics offers two ways to work together: a fixed-price AI Foundation Track and the AI Implementation Program. Whether you have one analyst or several data teams, the work starts where you are and builds what your team can keep running on its own, with the AI tools that fit your data stack and your company's policies. Proper AI-assisted analytics supercharges your analysts: AI does the heavy lifting, people make the calls and are responsible for data governance.
What AI-assisted analytics brings, for everyone involved
For the business
- Simple questions answered near-instantly, instead of in hours or days
- More questions answered; the backlog disappears
- Self-service around the clock in Slack or Microsoft Teams
- Same question, same answer, whoever asks
- Higher-quality answers: advanced statistics and data science within reach
For the data leader
- Productivity up several times over, without extra hires
- Ad-hoc requests drop by 90%, with less spill-over to data engineering
- More time for complex, strategic work (models, experiments, deeper analysis), which also gets a 4x productivity boost
- Faster onboarding of new analysts
- Low running cost per answer
- Documentation that keeps itself up to date
For the analysts
- Less repetitive work, more interesting analysis
- Skills that stay current and competitive in the job market
- More collaboration across analytics, data science and data engineering
- A more enjoyable way of working
For the organization
- Keeping up with competitors that already use AI
- Knowledge stays in the company
- Less risk: an approved AI setup instead of shadow AI
- AI output you can trust
AI Foundation Track
The foundation everything else builds on, in 2–4 weeks at a fixed price. You finish with:
- A score against the 10 stages of the Roadmap, and a prioritized plan
- Your baseline, measured the same way before and after AI
- Ground rules for AI: what’s allowed, and the right access controls
- Your first agreed metric definitions, each with an owner
- The right team design
- Your first AI win: a project or set of questions completed with AI
AI Implementation Program
Hands-on help to put the Roadmap into practice: connected data tools, agreed metric definitions and context, built-in quality checks, a self-serve data chatbot (see an example), and training for your team. Scoped from your Foundation Track and priced per proposal.
Covers the Roadmap stages your Foundation Track prioritizes. See the two ways to set up the team: data team design.
From first call to a team that runs it
- Free 30-minute call. Your situation, your goals, and whether it's a good fit.
- Foundation Track. 2–4 weeks at a fixed price: your score and prioritized plan, baseline, ground rules for AI, first metric definitions and your first AI win.
- Proposal. Clear scope, timeline and price for the program, based on the Foundation Track.
- Build in short sprints. Visible results every week or two, then handover so your team can run and improve it on its own.
Common questions
Which AI tools do you use?
Any AI tool that fits your data stack and your company's policies. The approach — context, quality checks, self-serve and standards — works regardless of the tool.
Is our data safe? What does the AI see?
Yes. Data access is agreed up front. The setup follows your security and privacy policies, and the AI only accesses the data it needs.
How long does it take?
Weeks, not months. The Foundation Track takes 2–4 weeks, and the first AI workflows go live as part of the Implementation Program.
What does it cost to run?
Usually little compared with an analyst's time. Costs depend on usage and the tools you choose.
How accurate is it?
Every result goes through quality checks. Before anyone outside the data team uses the AI, it's tested on 100–200 real business questions, with a target of more than 99% correct. Where the AI isn't sure, it should say so rather than guess.
Is it safe to connect AI to email and Slack?
Only with the right access controls: the AI sees only what the person asking is allowed to see, sensitive sources can be excluded, and everything follows your security and privacy policies.
Will this replace our analysts?
No. AI-assisted analytics removes the backlog, not the people. Analysts' focus shifts from heavy coding and building dashboards to quality checks, data governance and the analysis that matters most.