Verily Data is an agentic AI data strategist. It reasons about your business goals, interrogates your data, identifies what's missing, and tells you exactly what needs to be resolved before your ML or analytics initiative can move forward.
Organizations investing in AI and analytics - predictive models, operational dashboards, risk scoring - routinely hit blockers that could have been caught in advance.
Missing fields, inconsistent formats, and sparse historical records silently undermine any model or analytics initiative you try to build on top of them.
Teams don't know whether their data exports and systems have enough signal and structure to support predictive analytics. Usually they find out too late.
Without an upfront assessment, data engineering projects hit unexpected blockers weeks or months in. By then, the cost to fix them is at its highest.
You provide your goals and your data. The AI reasons through what you need, maps your objectives against what you actually have, and surfaces exactly what's blocking you. The same thinking a senior data scientist would bring, delivered automatically.
Share your business objectives and case management data exports (CSV or database). We define what success looks like.
Automated quality scoring, statistical profiling, anomaly detection, and cross-table relationship analysis across your dataset.
We map your goals against your actual data, identify what's missing, and score feasibility (High / Medium / Low) for each objective.
The AI agent applies domain knowledge and industry research to generate a prioritized remediation roadmap. Concrete actions, ranked by impact and effort, the way a senior strategist would advise.
Receive a PDF audit report and an interactive dashboard. Our team walks you through findings and next steps.
Every engagement produces concrete deliverables you can act on immediately.
A one-page overview of data health, top risks, feasibility scores per goal, and prioritized quick wins. Designed for decision-makers.
Comprehensive findings including data health scorecard, gap analysis by goal, feasibility scorecard, and severity-sorted issues with specific field-level detail.
Explore your audit results interactively. Filter gaps by severity, run what-if scenarios to see how fixing specific issues affects feasibility, and drill into any table or column.
Per-objective evaluation of whether your data can support each analytics initiative, with a HIGH / MEDIUM / LOW confidence rating and the reasoning behind it.
A 0–100 trust score for each table in your dataset, with a breakdown across completeness, consistency, and anomaly rate. So you know exactly where the weak spots are.
A ranked action plan showing which data gaps to fix first, with effort and impact estimates, risk flags, and the specific changes needed to unlock each blocked goal.
No commitment required. Tell us about your situation and we'll suggest the right approach.
We'll start with a short conversation to understand your goals and what data you have. From there, our AI data strategist scopes and runs the assessment, reasoning through your data the way a senior data scientist would. You get findings you can act on immediately.