Stop searching dashboards. Ask the business.
Eazy Insights AI
Eazy Insights AI is a governed AI analyst. It connects databases, warehouses, spreadsheets and approved SaaS data, answers natural-language questions with charts, tables and plain-language narratives, and supports follow-up investigation. A governed semantic layer defines metrics, dimensions, joins and fiscal calendars so revenue means one thing everywhere, and every answer writes an evidence ledger showing the data snapshot, definition and transformations behind it.
- 01Q: "Why did South India revenue fall last month?"
- 02Revenue ↓ 8.4% → Karnataka ↓ 13% → Enterprise ↓ 21%
- 03Driver: renewal loss · 3 accounts = 61% of the decline
- 04Evidence ledger: billing snapshot 14 min old · MRR contract verified
Connect your business data
Analysis across sources, under one set of definitions, without moving everything into a new warehouse first.
CRM and sales
Billing and finance
Support and tickets
Databases
Warehouses
Spreadsheets
Approved SaaS sources
Connections are read-only and scoped by role, and data stays where it is; the semantic layer describes it rather than copying it. Spreadsheets are treated as governed sources too, with owners and refresh rules.
Ask, investigate, explain
Questions rarely end with the first answer. Multi-turn analytical context lets a user keep pulling the thread.
- 01
Why did it fall?
- 02
Which customers?
- 03
Was this happening before?
- 04
What changed?
- 05
What should we watch?
Every follow-up inherits the context of the previous answer, including its filters and time period, so "which customers?" means the customers behind the 21% decline, not a new query. Investigations can be saved and shared.
Governed business metrics
Revenue should not mean different things to different departments. Every important metric has a definition, an owner, a source and permissions.
Definitions are written with your analysts during onboarding and owned by named people, so a change to how churn is calculated is a reviewed change with a version, not a silent edit in someone's dashboard.
- Semantic layer: metrics, dimensions, joins, fiscal calendars and business definitions
- Role- and row-level access with query audit
- Data-source traceability for every number
- Verified-answer library for recurring executive questions
Metric contract and evidence ledger
Every important KPI gets a machine-testable contract: definition, owner, allowed sources, freshness SLA, reconciliation checks and accepted tolerance. Every answer writes an evidence ledger. If the contract breaks later, previously generated decisions are flagged as potentially affected.
Monthly Recurring Revenue
- Owner
- Finance
- Definition
- Approved v3
- Source
- Billing database
- Freshness
- 14 minutes
- Reconciliation
- Passed
- Confidence
- Verified
- Ledger: snapshot, definition, filters, transformation, timestamp, source
- Alert: "3 previous analyses potentially affected"
Contracts are tested continuously, not only when a question is asked: freshness SLAs, reconciliation against source totals and definition changes are checked on a schedule, and a failing contract marks every answer that depended on it. The ledger is exportable, so an auditor or a board member can see precisely which data produced a decision on the day it was made.
From insight to decision
Analysis that reaches the people who act on it, on a schedule and when something changes.
Scheduled executive briefs
Threshold and anomaly alerts
Variance, trend and cohort analysis with explanations
Saved investigations and drill-down to records
Embedded analytics API and SDK for products and portals
Briefs and alerts use the same contracts and evidence ledger as ad-hoc questions, so an executive reading a Monday brief can open the evidence behind any number in one click.
Works with tools you already use
Eazy Insights AI connects to the systems you already run and to the wider Eazyware intelligence layer, so answers, documents, knowledge and metrics can move between products.
We've got answers
Everything you need to know about Eazy Insights AI before early access.
Can it write to our database?
No. It runs read-only under the requesting user's role with row-level security and query audit.
How do we trust the numbers?
Metric contracts define and test each KPI, and every answer carries an evidence ledger showing the snapshot, definition and transformations used.
What is a metric contract?
A machine-testable definition of a KPI with owner, sources, freshness SLA, reconciliation checks and tolerance; when it breaks, affected answers are flagged.
Do we need a warehouse first?
No. Well-modelled databases and spreadsheets work; a semantic layer is built with your analysts during onboarding.
Can we embed it in our product?
Yes, through the embedded analytics API and SDK, with tenant-aware permissions.
When is it available?
Eazy Insights AI is Live Soon; early-access customers start with five executive questions.
Sell trust, not charts.
Join early access and bring the five questions your board asks every month.
- No commitment; we reply within two working days
- Onboarding with your own data and documents
- Launch pricing for early-access customers
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