DATA & DECISIONS

A dashboard nobody opens isn't analytics. It's decoration.

Stop drowning in dashboards. Our AI doesn't just visualize your data, it surfaces insights you didn't know to look for and tells you exactly what to do next.

Why it matters

The case for doing this now.

Most companies aren't short on data. They're short on time to read it. The dashboards proliferate, the weekly reports get longer, and the actual decisions still come down to a gut call in a meeting because nobody had time to dig.

We build analytics that work the other direction: an AI layer that watches your data continuously, surfaces what changed and why, and tells you what to do - in plain English, in the channel you already use.

Intelligent data analytics that works the other direction: an AI layer watches your data continuously, surfaces what changed and why, and tells you what to do in plain English, in the channel you already use.

What’s included

How we ship this.

  1. Unified data layer

    Pipelines that pull together the systems you already pay for - CRM, billing, product analytics, ad platforms - into one queryable source.

  2. Custom dashboards built around your workflow

    Not a generic template. The metrics you actually run the business on, in the layout your team will actually open.

  3. Anomaly detection and proactive alerts

    Slack or email pings when something meaningful shifts - with the context, not just the chart.

  4. Natural-language analyst

    Ask questions in plain English and get back charts, breakdowns, and a written summary - without learning SQL or pinging the data team.

Data points

The numbers behind the case.

  • 12% / 80%

    of features drive 80% of usage across 615 enterprise apps

    Pendo Feature Adoption Report

  • 53%

    of SaaS licenses go unused or underused

    Productiv State of SaaS

  • ~20%

    of knowledge-worker time spent searching for information instead of acting on it

    Typical rangeAIIM / McKinsey range

  • Days → minutes

    typical compression in time-to-insight after AI analytics rollout

    Typical rangeWhat we've seen

  • <30%

    of legacy BI dashboards see weekly active use after launch

    Typical rangeIndustry estimate

  • 15%

    of daily work decisions projected to be AI-made by 2028

    Gartner Prediction

Sources are linked beneath each number. Items marked typical range come from our own engagements rather than a published study.

Where this shows up

What this looks like in practice.

An e-commerce brand running on Shopify, Klaviyo, and Meta Ads

We unified spend, attribution, and product margin into one daily view, and added an AI summary that flags which SKUs and creatives are quietly losing money. Decisions about ad budgets moved from a monthly meeting to a same-day shift.

Representative engagement

A B2B SaaS company drowning in feature-usage data

Built a usage map showing which 12% of features were driving real engagement and which were dead weight. The product team reprioritized the roadmap and killed two underused modules without a guess.

Representative engagement

Guides to help you decide

  • AI for Ecommerce

    AI for ecommerce, job by job: pre-sales questions, WISMO and returns, product content, search, customs paperwork, and reporting, plus how to test a store bot.

  • AI for Manufacturing

    AI solutions for manufacturing that hold up on the floor: RFQ intake, SOP search, maintenance tickets, NCRs, ERP questions, private AI, and scaling IIoT pilots.

  • AI for Marketing Agencies

    AI for marketing agencies: automate client reporting, scale creative inside brand guardrails, tighten briefs and QA, and sell AI search work to clients.

Next step

What would you do if your data answered back?

Bring us the question your dashboards never quite answer. We'll prototype an AI analytics layer against your real data in days, not quarters.

Intelligent Data Analytics | Buzzed Technologies