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Business Intelligence · head to head

Pigment vs Zenlytic

Pigment logo

Pigment

Business Intelligence

Enterprise business planning platform for finance, sales and workforce modelling

From
On request
Rated
-
Full reviewWebsite
Zenlytic logo

Zenlytic

Business Intelligence

Conversational analytics on a governed semantic layer that shows you the SQL it ran

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Pigment no pricing is published and the structure has three moving parts, platform fee, use-case fees and tiered seats, so two companies of the same size can pay very different amounts and neither can benchmark the other.; Zenlytic answer quality is bounded by the semantic model, so a team without a maintained dbt project and metric definitions must complete a modelling project before the AI is useful at all.
  • They diverge on capability: Pigment covers Dimensional modelling, Zenlytic covers Zoe conversational agent.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Pigment and Zenlytic actually diverge.

Attributes where Pigment and Zenlytic differ
AttributePigmentZenlytic

Identical on both: starting price (On request), pricing model (quote), free tier (No), platforms (Web), user rating (Not yet rated), category (Business Intelligence).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Pigment

  • Dimensional modelling
  • Scenario planning
  • Data connectors
  • Application blocks
  • Reporting and boards
  • Access control
  • Audit trail
  • AI assistance

Only in Zenlytic

  • Zoe conversational agent
  • YAML semantic layer
  • LookML import
  • Row and column permissions
  • Dashboards
  • dbt integration
  • Embedded analytics
  • Query transparency

What people use each for

The jobs each tool is most often brought in to do.

Pigment

  • A finance team retiring a fragile Excel consolidation that no one can audit and only one person can runnot Zenlytic
  • Sales operations modelling quota, territory and headcount capacity against a revenue plan in the same system finance usesnot Zenlytic
  • A company that needs monthly re-forecasting fast enough to run scenarios live in the leadership meetingnot Zenlytic
  • Replacing an ageing Anaplan estate where the model has become unmaintainable and per-workspace costs have crept upnot Zenlytic

Zenlytic

  • A data team of three fielding sixty ad hoc requests a week from operators who could answer them in chat insteadnot Pigment
  • An ecommerce company where merchandisers need cohort and margin questions answered without waiting for an analystnot Pigment
  • A Looker customer looking for an exit that can import existing LookML rather than remodel from scratchnot Pigment
  • A finance team that needs every AI-generated number to show its SQL before it goes in a board packnot Pigment

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Pigment

  • No pricing is published and the structure has three moving parts, platform fee, use-case fees and tiered seats, so two companies of the same size can pay very different amounts and neither can benchmark the other.
  • Cost scales with planning processes rather than with company size, so a successful first deployment creates internal demand that directly increases the bill at renewal.
  • It requires a modelling owner. Without a person who understands dimensional design, teams rebuild spreadsheet patterns in Pigment and inherit all the maintenance problems they were trying to escape.
  • Implementation is partner-led and measured in months, so the payback horizon is long compared with lighter FP&A tools that a controller can configure alone.
  • The connector library covers major systems well but the long tail is thinner than the incumbents, and industry-specific source systems often need a warehouse or a file drop in between.

Zenlytic

  • Answer quality is bounded by the semantic model, so a team without a maintained dbt project and metric definitions must complete a modelling project before the AI is useful at all.
  • It is a small venture-funded company in a category that Snowflake, Databricks and Microsoft are all building into natively, which is a real procurement risk on a multi-year contract.
  • Pricing is not published and is negotiated per deal, so small buyers have no benchmark and no leverage.
  • The visualisation and dashboard layer is thinner than established BI tools, so teams wanting pixel control over reporting will find it limiting.
  • It assumes a cloud data warehouse; organisations with data spread across operational databases and spreadsheets have to consolidate first, which is the expensive part of the project.

Pricing, plan by plan

Pigment

On request
  • Pigment platform$undefined/year
    • Platform fee plus per use-case fees
    • Licences tiered as editor, contributor and explorer
    • No free tier and no self-service signup

Zenlytic

On request
  • Zenlytic$undefined/year
    • Annual contract quoted by seats and deployment
    • Semantic layer, dashboards and Zoe included
    • Embedded analytics licensed separately

Which should you pick?

Choose Pigment if

  • You need dimensional modelling.
  • You also want scenario planning.
Pigment review

Choose Zenlytic if

  • You need zoe conversational agent.
  • You also want yaml semantic layer.
Zenlytic review

Questions people ask

Is Pigment or Zenlytic better?
Neither clearly leads. Pigment starts at On request and Zenlytic at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Pigment or Zenlytic?
Pigment starts at On request and Zenlytic at On request.
Does Pigment or Zenlytic run on more platforms?
Both run on Web, so platform support will not decide this one for you.
What is Pigment best used for?
Pigment is most often used for a finance team retiring a fragile excel consolidation that no one can audit and only one person can run, sales operations modelling quota, territory and headcount capacity against a revenue plan in the same system finance uses, a company that needs monthly re-forecasting fast enough to run scenarios live in the leadership meeting, replacing an ageing anaplan estate where the model has become unmaintainable and per-workspace costs have crept up. Of those, a finance team retiring a fragile excel consolidation that no one can audit and only one person can run and sales operations modelling quota, territory and headcount capacity against a revenue plan in the same system finance uses are not what Zenlytic is typically brought in for.
What can Pigment do that Zenlytic cannot?
Pigment covers Dimensional modelling, Scenario planning, Data connectors, Application blocks. Zenlytic covers Zoe conversational agent, YAML semantic layer, LookML import, Row and column permissions.

Answered from the vendors’ own pages

Pigment: Does Pigment publish prices?

No. Expect a quote combining a platform fee, fees per planning use case, and seat licences split into editor, contributor and explorer tiers.

Zenlytic: Does Zenlytic publish pricing?

No. Contracts are quoted annually based on seats and deployment scope.

Pigment: Is Pigment an alternative to Anaplan?

It is positioned directly against Anaplan and much of its customer base is migrating from it, mainly citing modelling readability and recalculation speed.

Zenlytic: Can it read my Looker model?

Yes, it imports LookML, which is the main reason Looker customers evaluate it.

Pigment: Can we use it without consultants?

In practice most deployments use Pigment or a partner for the initial build. Ongoing model changes can be handled in-house once someone owns the modelling discipline.

Zenlytic: Does it write arbitrary SQL against my warehouse?

No. Queries are constrained to the semantic layer, and the generated SQL is shown with every answer.

Pigment: Where is data hosted?

Pigment is a European vendor with regional hosting options, which is often the deciding factor for EU buyers with data residency requirements.

Zenlytic: Do I need dbt?

Not strictly, but the product is designed around a modelled warehouse and works poorly without one.

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