The language of trusted data and decisions.

The rules determining who can access data, when and under what conditions.

Access policies protect the business from regulatory, reputational and competitive risk. When policies live inside the data product, they are enforced consistently, regardless of who or what is asking.

Governance embedded into how data products are created, accessed and consumed.

Governance that is embedded into the way data products are created, accessed and consumed, rather than applied only after the fact. Definitions, quality rules, access policies and lineage live inside the data product so trust is visible to every consumer, including AI agents.

Applying policy, explainability and accountability to AI where decisions are actually made.

Governing the model in isolation is insufficient. Governance must travel with the AI into the decision moment, visible to the decision owner, recorded for audit, and enforceable in flight.

The trusted, governed interface that supplies AI with business context, policy and lineage.

A Data Plugin for AI is the layer that plugs enterprise meaning into AI systems. Instead of pointing a model at raw tables, it serves a governed data product complete with business definitions, access policy, lineage and trust signals, so the AI can reason and act on information the business already trusts.

The roles, ownership, governance and lifecycle that make data products repeatable.

The cost, speed and trustworthiness of data products are determined by the operating model around them, not the platform underneath. Operating model beats tooling.

An environment for creating, governing and sharing trusted data products.

A workbench combines the modeling, governance and publishing capabilities a business team needs to deliver a trusted data product end-to-end, without handing off to a separate data engineering team for every change.

An organization that improves decisions through trusted data products and governed operating models.

An organization that uses trusted data products, clear decision ownership and governed operating models to improve decisions across the business.

The combination of people, processes, data products, governance and AI supporting decisions.

Decisions are never made in isolation. The ecosystem around a decision determines how fast, how confidently and how consistently it can be made.

The guarantee that every choice, human or AI, is valid, consistent and backed by evidence.

The structural metric and operational guarantee that an organization’s choices are valid, consistent, and completely backed by evidence. Rather than treating integrity as a passive data-cleaning exercise, it elevates governance to an execution discipline, ensuring humans and AI operate on identical parameter guardrails.

Product · Latttice & Lenz Integration

A continuous, auditable record connecting raw data to the action it permitted.

The active, point-in-time record of how raw information was authorized, transformed, and contextualized to permit a specific business outcome. It provides an auditable trail showing not just where data went, but why an action was permitted.

Product · Latttice Workbench

The sequence of activities required to move from information to action.

Most decisions span people, systems and time. Mapping the workflow exposes where trust breaks down, where latency creeps in and where AI can add the most leverage.

The Data Tiles belief that data, governance and AI only create value when they improve decisions.

Every Data Tiles capability, trusted data products, active governance, Latttice, Lenz, exists to enable better decisions. Data that does not change a decision does not change an outcome.

Governance evidence automatically generated during creation and consumption.

Evidence by default replaces manual audit prep with a continuous stream of governance artefacts. When evidence is a byproduct of normal work, audits stop being events and become reports.

The capability that combines data from multiple governed sources into reusable data products.

Fusion is how Latttice turns scattered, governed sources into composed, trusted data products, preserving lineage and policy across every input so the output is itself trustworthy.

A model where humans supervise AI operations and intervene when necessary.

Human-on-the-loop scales AI without removing accountability. The agent acts within policy; humans monitor, audit and intervene when patterns or exceptions demand it.

The Data Product Workbench that enables business teams to create trusted, governed data products without code.

Latttice puts data product creation, governance and consumption in the hands of the business, with active governance, trust signals and AI built in. The platform expression of the decision-driven operating model.

The capability for shaping and refining data products while preserving governance and trust.

Transform lets business teams prepare and refine data products with governance applied in line, so changes are visible, auditable and never compromise the trust envelope.

Governance performed after the fact through audits, remediation and manual review.

Passive governance is expensive, slow and chronically out of date. It treats governance as a control layer bolted on top of data, rather than a property of the data product itself.

The moment or workflow where trusted data is needed to support a decision or action.

The moment, workflow or business context where trusted data is needed to support a decision, recommendation or action.

Encoding governance policies into technology so they are enforced automatically.

Policy as code makes governance scalable. Instead of relying on memory, training and goodwill, policies travel with the data product and are applied uniformly every time it is used.

Application of access, usage, privacy and governance rules so data is consumed safely.

The application of access, usage, privacy, security and governance rules to ensure data is consumed safely and appropriately.

Identifying and labeling data that needs additional protection.

The process of identifying and labeling data that requires additional protection, such as personal, financial, health, commercial or regulated information.

The governance, lineage, ownership, policy and quality context that travels with a data product.

Wherever a trusted data product is consumed, Pin Board, Convo, AI agent, downstream tool, its trust envelope travels with it. Trust is not a property of the source system; it is a property of the data product itself.

Visible indicators of freshness, quality, lineage, ownership and policy at the point of use.

Trust is only useful if the consumer, human or AI, can see it without leaving the workflow. Trust signals turn governance from a back-office activity into an executive-facing one.

Indicators that help users and AI systems judge whether a data product is reliable and endorsed.

Indicators that help users and AI systems understand whether a data product is reliable, endorsed, governed and actively used.

Trusted, governed, explainable data available where decisions are made.

Trust changes everything. When governed, explainable data shows up at the point of decision, business users and AI agents can act with confidence, without re-asking the data team or second-guessing the number.

A governed, owned and transparent data product that consumers and AI systems can confidently use.

Trust is what separates a data product from a dataset. Trusted data products carry visible lineage, ownership, policy and quality signals, so executives and AI agents can rely on them without re-asking the data team.