Latttice — the Data Product Workbench for Collibra, now on the Collibra MarketplaceLatttice — the Data Product Workbench for Snowflake70% Less Complexity with LattticeDeliver Trusted Data 80% FasterLower the Cost of Building and Operating Data Products by 70%Latttice is available where business teams work — Slack, Excel, LattticeGPTLatttice the Data Product Workbench brings trusted, fit-for-purpose data to the point of decisionsLatttice the Data Product Workbench is the bridge between the Business and Data TeamsLatttice delivers active governance at the point of data access, so trusted data products are created, controlled, and used with confidenceDesigned in North Carolina, USA
Governance

Governance embedded into every data product.

Latttice operationalizes governance across the full data product lifecycle — from creation through consumption.

LineageAccess ControlPolicy WorkflowsTrustAI Readiness
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CREATE DATA PRODUCT · GOVERNANCE
Engineering
Frontend
Syndicated Data Product
A standard, internal data product for organizational use.
Data SensitivityPublic
Data Product Workbench for Colliers
✦ AccelerateCreate Data Product
The Six Pillars

Governance built into every data product.

Not a layer above. Not a checklist beside. Governance is woven into how products are designed, published, consumed, and audited.

Policy Enforcement

Active policies executed at query, API, and share time — not buried in a catalog.

Lineage

End-to-end traceability from source systems to point of decision, automatically generated.

Ownership

Clear accountability for every product, domain, and dataset across the enterprise.

Access Control

Row, column, and cell-level RBAC and ABAC tied to identity providers and context.

AI Readiness

Signals that flag whether a product is safe, governed, and reliable for AI consumption.

Trust

Quantified confidence based on quality, freshness, lineage depth, and usage signals.

Governance Capabilities

Eleven controls. One operating model.

Every capability is enforced where data is produced, shared, and consumed — with a clear enterprise outcome attached to each.

01

Ownership

What it does

Every product, domain, and dataset has a named owner and steward, synced from your IdP and HRIS.

Why it matters

Without accountability, governance breaks down — questions go unanswered and risk accumulates silently.

Enterprise outcome

Audit-ready accountability across thousands of products with zero spreadsheets.

02

Lineage

What it does

Column-level lineage automatically derived from queries, pipelines, and product definitions.

Why it matters

Teams need to know where data came from before they can trust or change it.

Enterprise outcome

Faster impact analysis, fewer broken dashboards, defensible regulatory reporting.

03

RBAC

What it does

Role-based access tied to identity providers, groups, and organizational structure.

Why it matters

Roles change constantly — access must follow the org, not lag behind it.

Enterprise outcome

Least-privilege access at scale without manual ticket queues.

04

ABAC

What it does

Attribute-based policies that adapt to user, region, purpose, and runtime context.

Why it matters

Static roles can't express modern policy: residency, consent, purpose limitation, contractual scope.

Enterprise outcome

One policy expression covers thousands of contextual access decisions.

05

Fine-Grained Access

What it does

Row, column, and cell-level masking and filtering enforced at query time.

Why it matters

Most sensitive data lives inside otherwise-shareable tables — coarse access forces over-restriction.

Enterprise outcome

Broader, safer data access — analysts get the rows they need, nothing more.

06

Policy Enforcement

What it does

Active policies executed in real time across queries, APIs, shares, and AI calls.

Why it matters

Policy that lives in a document is policy that gets bypassed.

Enterprise outcome

Provable enforcement — every access evaluated, every decision logged.

07

Sensitivity Classification

What it does

Automatic detection and tagging of PII, PHI, financial, and regulated data.

Why it matters

You can't govern what you haven't classified — and manual tagging never keeps up.

Enterprise outcome

Continuous, accurate classification across the full estate as data evolves.

08

Data Contracts

What it does

Versioned schema, SLA, and semantic contracts between producers and consumers.

Why it matters

Silent breaking changes destroy downstream trust and force defensive engineering everywhere.

Enterprise outcome

Stable interfaces, predictable change management, fewer 2 a.m. pipeline pages.

09

Trust Scoring

What it does

Quantified score from quality, freshness, lineage depth, ownership health, and usage signals.

Why it matters

Consumers need a fast signal to choose between similar products without deep investigation.

Enterprise outcome

Faster confident decisions and a measurable improvement loop for product owners.

10

AI Readiness Scoring

What it does

Per-product readiness signals covering grounding, freshness, governance, and approved AI use.

Why it matters

Models inherit the risk of their inputs — ungoverned data produces ungovernable AI behavior.

Enterprise outcome

Safe, certified inputs for agents, copilots, and downstream AI systems.

11

Lifecycle Governance

What it does

Stage tracking from draft → certified → deprecated, with policy that adapts at each stage.

Why it matters

A product's risk and obligations change as it matures — governance must change with it.

Enterprise outcome

Healthy estate hygiene, controlled deprecation, and no orphaned products in production.

Operational Governance

Enforced at every point of use.

Policy is evaluated where data lives and moves — at discovery, design, publish, consumption, and audit. No drift. No gaps.

ENFORCED BY DEFAULT
  • Policies execute on every query, API, and share — no exceptions.
  • Audit-ready evidence generated automatically for every access event.
  • Aligned with SOC 2, GDPR, HIPAA, and internal compliance frameworks.
STAGE 1
At Discovery

Sensitive products surface with classification, ownership, and access requirements visible upfront.

STAGE 2
At Design

Policy guardrails enforced as products are composed — no path to publish a non-compliant product.

STAGE 3
At Publish

Quality gates, approval workflows, and certification checks executed before a product goes live.

STAGE 4
At Consumption

Every query, API call, and share evaluated against active policy in real time.

STAGE 5
At Audit

Evidence generated automatically for every access — SOC 2, GDPR, HIPAA aligned.

Lineage

Trace every value to its source.

Column-level lineage generated automatically — across pipelines, products, BI, APIs, and AI consumers.

Latttice Surface Visual Model showing column-level lineage between CRM Contacts, AML Screening, and Core Customer Information data products
Ownership

Clear accountability, end to end.

Every product has a named owner, a steward, and a domain. Approvals, changes, and incidents route automatically.

LP
Lena Park
Customer · EMEA
Product Owner
MV
Marcus Vega
Privacy & Compliance
Data Steward
AT
Aki Tanaka
Reliability
Platform SRE
Access Control

The right data, for the right purpose.

Identity, role, attribute, and purpose — combined into a single, enforceable model. Down to the cell, evaluated at query time.

RBAC

Role-based access tied to your identity provider and org structure.

ABAC

Attribute-based policies that adapt to user, purpose, and context.

Fine-Grained

Row, column, and cell-level enforcement at query time.

Classification

Automatic tagging for PII, PHI, financial, and regulated data.

Purpose Binding

Bind access to declared business purpose, not just identity.

Sensitivity

Masking, redaction, and tokenization driven by classification.

AI Readiness

Governance that scales to AI.

AI multiplies the cost of bad governance. Latttice ensures models, agents, and prompts only consume products that are owned, lineage-tracked, and policy-cleared.

  • Inputs and outputs governed as first-class assets, with lineage to source.
  • Every model and agent declares purpose, owner, and consumed products.
  • Sensitive data masked or restricted before reaching prompts and embeddings.
  • Audit trail captures who accessed what, for which model, and for what purpose.
AI READINESS · churn_agent
CERTIFIED
Inputs governed
4 / 4 products
Sensitive data masked
PII, PHI
Purpose declared
Retention modeling
Lineage depth
12 hops · 100% covered
Prompt audit
Every call logged
Continuous re-evaluation — readiness updates with every upstream change.
Trust, Quantified

Trust isn't a promise — it's a measurement.

Every product carries a live trust score, policy coverage, and audit posture — visible to every consumer, every time.

98
Trust Score
Quality + freshness + adoption
100%
Policy Coverage
Across analytics, APIs, and AI
0
Manual Approvals
For certified, in-policy products
24/7
Continuous Audit
Evidence captured automatically

See governance in execution.

Walk through a live data product — from policy authoring to enforced consumption in BI, APIs, and AI agents.