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Wayam AI
Modern BI

Setu™

setu - bridge, a crossing built to be used

Legacy BI to modern analytics: migration, parity, and AI-ready insight.

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At a glance

Category
Modern BI
Theme
Legacy-to-Modern BI
Industries
Technology, Financial Services, Retail & CPG
Capabilities
5 composed
Pairs with
Bodham

Who it is for

  • Enterprises retiring legacy BI toward modern platforms
  • BI and data-platform teams consolidating analytics estates
  • Leaders standing up Fabric data agents or Databricks Genie

Systems it sits on

Tableau · Power BI · Microsoft Fabric · Looker

Also used in

TechnologyFinancial ServicesRetail & CPG

Pairs with

Bodham

Abstract modern BI visual showing legacy analytics resolving into AI-ready panels

Explainer

Setu in two minutes

A narrated walkthrough of the problem, how Setu works, and what changes. Captions are available in the player.

Setu: Legacy BI retired. Parity proven. Ready for AI.Running time 2:10

Setu is the legacy-to-modern BI accelerator: move enterprises off aging dashboard estates onto modern analytics environments, validate parity, recover license spend, and activate AI/BI use cases such as Microsoft Fabric data agents and Databricks Genie. Tableau and peer suites are source estates within that narrative, not Setu's identity.

The problem

Enterprises are stuck on legacy BI estates that burn license spend and block the move to modern platforms and AI-native analytics.

The outcome

A clear path from legacy to modern BI: automated migration with parity, license recovery, and activation of AI/BI agents on the target platform.

How it works

How Setu works

  1. 01

    Inventory the legacy estate

    Dashboards, data sources, and real usage are catalogued so the program is scoped on evidence.

  2. 02

    Auto-migrate

    The engine converts 80–90% of dashboards to the target modern BI platform automatically.

  3. 03

    Validate parity

    Migrated output is compared against the source until it matches.

  4. 04

    Activate AI/BI

    Data agents and conversational analytics on Fabric, Genie, and peers unlock the next layer of insight.

Abstract icon for the Legacy Estate Intake module of Setu

Module 01

Legacy Estate Intake

Inventory dashboards, data sources, and real usage across the legacy suite.

  • 02

    Auto-Migration Engine

    80–90% of dashboards converted automatically.

  • 03

    Parity Validation

    Verify migrated output matches the source.

  • 04

    AI/BI Activation

    Stand up data agents on Fabric, Databricks Genie, and peer platforms.

dashboards migrated
0+dashboards migrated
to completion
0 weeksto completion
license savings
$0Mlicense savings

Verified proof

Delivered engagements for Setu. These claims are verified, not modelled scenarios.

BI migration proof visual with legacy dashboards reorganized into a modern analytics wall

Global Enterprise

Verified outcome

1,200 Tableau dashboards retired in six weeks

A sprawling Tableau estate blocked the move to modern BI and burned license spend while AI/BI pilots stalled.

Tableau dashboards migrated in 6 weeks
0+Tableau dashboards migrated in 6 weeks
license savings
$4.2Mlicense savings
Read the verified outcome

Use cases

Where Setu runs

All 5 in the library

Finance

Retiring a Global Tableau Estate Ahead of a License Renewal

A multinational industrial group runs more than 1,200 Tableau dashboards across eleven business units, with an enterprise license renewal due in two quarters.

Analytics

Consolidating Four Analytics Platforms After an Acquisition

A financial services group completing three acquisitions in two years inherited four separate BI platforms, each with its own semantic layer and refresh schedule.

Analytics

Unlocking Conversational Analytics on a Modernized Estate

A retail group finished a warehouse modernization but left its reporting layer untouched, so business users still wait on analysts despite the new platform underneath.

Quality & Compliance

Proving Parity on Regulated Financial Reporting Before Cutover

A bank migrating its risk and finance reporting cannot cut over until an internal audit function accepts that migrated figures are identical to the source.

Finance

Recovering License Spend from a Dormant Dashboard Estate

A manufacturing group pays per-seat and per-server BI licensing against an estate that has grown for nine years without anyone retiring anything.

Integrations

TableauPower BIMicrosoft FabricLookerSnowflakeDatabricksDatabricks Genie

Ideal for

  • Enterprises retiring legacy BI toward modern platforms
  • BI and data-platform teams consolidating analytics estates
  • Leaders standing up Fabric data agents or Databricks Genie
  • Finance owners chasing license savings on the way through

Capabilities

Setu composes these capabilities from the shared Agent Platform layer. The same atoms power the rest of the portfolio, so adopting a second accelerator reuses the integration work rather than repeating it.

Composition

Setu is assembled from shared platform atoms. Hover a partner to see what you reuse on the next deployment.

Pairs with

Ingest

System Connectors
MCP-connected reads and writes against the ERP, MES, PLM, CRM, and warehouse systems already in place.

Ingest

Document Intelligence
Structure from unstructured sources: regulatory bulletins, specifications, contracts, claims, and reports.

Govern

Parity Validation
Migrated or regenerated output compared against its source until it matches, so cutover is signed off on proof.

Act

Workflow Orchestration
Specialist agents coordinated across a multi-step process, each handing structured context to the next.

Reason

Natural-Language Query
Business questions converted into validated queries, run against governed data, and returned as answers.

Pairs with

Conversational Analytics

Bodham

Ask the question in plain language; get validated SQL, charts, and an answer.

FAQ

Is Setu only a Tableau migrator?

No. Tableau is a source estate within Setu's legacy-to-modern BI positioning. The accelerator provides the path to modern analytics and AI/BI activation.

What migration rate can we expect?

Typically 80–90% of dashboards convert automatically; the remainder are prioritized for guided manual work.

Which modern BI and AI targets are supported?

Targets include Power BI, Microsoft Fabric, Looker, Snowflake, and Databricks, including Fabric data agents and Databricks Genie. The stack is confirmed during scoping.

How do you prove the migration is correct?

Parity Validation compares migrated dashboards against the source, so you sign off on evidence, not hope.