Analytics That Understand Your Business
Business Intelligence Made Simple
Traditional analytics tools require you to know what to look for. Genesis Analytics understands your business and surfaces insights automatically. Ask questions in plain English, get answers instantly, and let AI identify trends and opportunities you might miss.
Intelligent. Automatic. Actionable. Analytics that work for you, not the other way around.
What Makes Genesis Analytics Different
Natural Language Queries
Ask questions like "How are sales trending this month?" or "Which projects are at risk?" Get answers, not just charts.
Automatic Insight Detection
AI identifies patterns, anomalies, and opportunities without you having to dig through data
Real-Time Data
Live connections to your projects, apps, and external services. Always current, always accurate
Predictive Analytics
Understand what's likely to happen next based on historical patterns and trends
Analytics Capabilities
Business Metrics
- Revenue and growth tracking
- Customer acquisition and retention
- Team productivity and utilization
- Financial health indicators
Performance Analysis
- Project completion rates
- Task velocity and efficiency
- Resource allocation insights
- Timeline and milestone tracking
Sales Intelligence
- Pipeline health and velocity
- Conversion rate analysis
- Lead source performance
- Revenue forecasting
Operational Insights
- Process efficiency metrics
- Quality and error rates
- Capacity planning
- Service level indicators
How It Works
1. Connect Your Data
Pull from Taskade projects, Google Sheets, databases, or any of 100+ integrations
2. Ask Questions
Use natural language to query your data: "Show me sales trends" or "Which customers are most engaged?"
3. Get Insights
AI analyzes patterns, surfaces anomalies, and provides actionable recommendations
4. Take Action
Insights connect to your workflows, triggering automations and alerts when attention is needed
The Intelligence Advantage
Before: Hours of data analysis, manual report generation, reactive decision-making
After: Instant insights, automatic trend detection, proactive recommendations
- Questions answered in seconds, not hours
- Patterns identified automatically
- Predictions that help you plan ahead
- More time for strategy, less time analyzing
📚 Resources & Getting Started
Ready to unlock intelligent analytics? Explore these resources:
🚀 Get Started
- Taskade Genesis — Build AI-powered analytics from one prompt
- Create Your First App — Step-by-step tutorial
- Community Templates — Browse and clone analytics dashboards
🧬 Understand the DNA
- How Genesis Works: Workspace DNA — Your workspace becomes your backend
- 🤖 Custom AI Agents — The Intelligence Pillar
- 🧠 Projects & Databases — The Memory Pillar
- ⚡ Automations & Workflows — The Execution Pillar
📖 Related Articles
Be honest about which analytics problem you have
There are three genuinely different problems that all get called analytics, and using the wrong tool for yours is why so many reporting projects stall.
| Your situation | The right tool | Why |
|---|---|---|
| The numbers you care about live in the work itself: pipeline, projects, requests, bookings | Taskade AI analytics | The data is already in your workspace, so there is nothing to extract, and agents can watch it continuously |
| One dataset, one question, once | A spreadsheet | Do not build a system for a question you will ask once |
| Warehouse-scale data with governed definitions and a data team | A dedicated business intelligence platform | Modelled semantic layers, governance, and scale are what those platforms exist for |
Taskade is squarely the first row. It is operational analytics over live work, not a replacement for a warehouse, and a page that pretended otherwise would waste your time.
Asking in plain English, concretely
The answer comes from live workspace records, so it reflects the state of the business at the moment you asked rather than the state of a nightly extract. That makes the follow-up question the valuable part: you ask why, and the agent can look at the underlying records rather than only at an aggregate.
Questions that work well:
- "Which deals have not moved in more than two weeks, and who owns them?"
- "How does this month's request volume compare with last month, by category?"
- "Which clients are consuming the most support time relative to what they pay?"
- "What changed in the pipeline since Monday?"
The last one is the one people underrate. A running commentary on what changed is more useful than a chart most days, and it is only possible when the analytics layer sits on live data.
From answer to action
An insight nobody acts on is decoration. Because analytics live in the same workspace as your automations, a threshold can trigger something: an alert to the right person, a scheduled digest, a task created against the owner of a stalled deal. That closes the loop that most business intelligence stacks leave open.
Frequently asked questions about AI analytics
Can I really ask questions about my data in plain English?
Yes. You ask the question the way you would ask a colleague, and the answer is drawn from your live workspace records rather than from a pre-built report. You can keep asking follow-ups, which is the difference between a conversation and a dashboard.
Where does the data come from?
From your workspace projects, from tools connected through integrations, and from records that automations write back after they run. Because these are the same records your team edits, the analysis reflects live work rather than a copy that drifted.
Is this a replacement for Power BI or Tableau?
No, and it should not be sold as one. Those platforms exist for warehouse-scale, governed, modelled reporting with a data team behind them. Taskade covers the far more common case of a team that needs to understand its own operational data without standing up a data stack at all.
Can AI find trends I did not ask about?
Yes. An agent can watch a metric continuously and surface anomalies, drift, and patterns without being asked each time, which is the part a dashboard cannot do because a dashboard waits for someone to look at it.
Can I get an alert when a number moves?
Yes, as an automation. You set the threshold and the automation notifies the right person, creates a task, or posts to a channel. Automations run on a durable execution engine, so an alert that fails to deliver is retried rather than silently dropped.
Can I analyse a spreadsheet with AI?
Yes. Bring the spreadsheet in as a project and the records become part of your workspace, at which point you can ask about them, build views over them, and let automations act on them. Read migrating spreadsheets to AI dashboards.
How much data can I analyse?
This is operational analytics over workspace records rather than warehouse-scale analytics, so it is sized for the volume a working team generates: deals, projects, requests, bookings, and submissions. If your question genuinely requires scanning hundreds of millions of rows, that is a warehouse job and you should use a warehouse.
Who can see the analytics I build?
Whoever their role allows. role-based access from Owner to Viewer governs the underlying records, so analysis cannot reveal data a person could not open directly. That means you can share a view with a client or a contractor without building a stripped-down copy for them.
Can I schedule a report to send automatically?
Yes, as a scheduled automation that assembles the summary and sends it through your connected mail or chat tool. Because an agent writes it, the digest can explain what changed rather than just attaching numbers.
Does it connect directly to my production database?
No, and that is a feature rather than a gap. Analysis runs over your workspace records and the sources you connect through integrations, so there is no credential to a production database sitting in a chat tool and no query an AI could run against your live system. If your question genuinely requires querying a production database, that is a job for a tool designed to do it under supervision.
Can the AI change my data when I ask it a question?
Asking a question reads; it does not write. Changes happen through actions you set up deliberately, as automation steps or agent tools you enabled, and those are governed by role-based access from Owner to Viewer. Keeping the asking path read-only is what makes it safe to let people who are not analysts ask anything they want.
What is the difference between AI analytics and an AI dashboard?
A dashboard is a standing surface for metrics you already know you watch. Analytics is for the questions that change, asked in plain English. Most teams want both, and they read the same live records. Start on the builder, see 10 AI dashboards you can clone, or read about ops dashboards for lean teams.