CustomerDomainKPIOwnerAccountTermSourceRule
    Agentic Context Layer

    Metagem — the enterprise context layer for agentic AI and BI. AI is moving into the enterprise.
    No one told it your house rules.

    We align your data and knowledge landscape.
    Pinpointing the quality gaps that cost you.
    The exhaust is a governed AI context layer.
    Sovereign AI foundations, in-house.
    For lean teams & messy data Runs in your cloud Works across MicrosoftAnthropicOpenAI
    Talk to our team →How does it work?
    Powered byimec
    NVIDIA Inception ProgramMicrosoft for Startups
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    Insight detectedmetagem.ai

    30 open deals chased on products currently out of stock.

    SAP×Salesforce· out of sync

    Why enterprise data landscapes are not ready for AI agents

    Your data landscape isn't ready for AI Agents & 'Talk to your Data'.
    Decades of systems. No shared language.
    'Active customer' has three definitions spread across four systems.
    This needs fixing first.
    What works: focus on the critical 10%.
    The data that moves the business.
    That's where we come in.
    01

    Plug data, systems & knowledge

    Plug into your systems, data and institutional knowledge: Sharepoint, Confluence, Salesforce, Databricks, Fabric, Tableau, and the rest of your stack. Read-only, no data leaving your premises.

    SAP
    Salesforce
    SharePoint
    Confluence
    Microsoft Fabric
    Tableau
    + any system
    02

    Build Enterprise Context Graph

    Years of data governance work delivered in the first months: a live, automatically stitched map of every data field, document, asset and business term.

    SAPSharePointRevenue PolicyGL AccountCustomerNet RevenueGross Margin
    03

    Spot and fix quality gaps

    Agents that dig in and show you the data quality gaps, and how they impact business. Prioritized against what really drives €€€.

    Discover how our data quality audit ties to ROI
    Priority
    Quality issues in critical reports
    12 datasets feeding board KPIs
    High
    Revenue definition drift
    Finance vs. Sales mismatch
    Medium
    Conflicting KPI lineage
    Duplicate definitions across domains
    Low
    04

    Trusted Context available anywhere

    Your team remediates the priorities to enrich the graph. Our engine makes it available for any downstream AI, BI or other initiative.

    How context engineering grounds agents and BI
    metagem
    Microsoft Copilot
    OpenAI
    Anthropic
    Custom Agents
    Microsoft Purview
    SAP
    Systems of Record
    Tableau
    Power BI
    BI tools & semantic layers
    SharePoint
    Confluence
    Knowledge bases

    Basta. Time to go beyond co-pilots to drive real value.

    Talk to our team

    For data teams that are ready to leap

    01

    A business case for trusted data

    Metagem's agents surface where your data systems and your business disagree, estimate the impact, and work with you on a fix.

    02

    Populated from day one

    It reads your documents and systems and builds the map itself. Your team validates the critical 20% instead of curating a catalog by hand.

    03

    One layer across every system

    SAP, Microsoft, legacy. Validated context syncs to the tools you already use: Catalog, BI tool, your AI pipelines.

    04

    Sovereign-by-design. Data stays where it is

    Metagem reads structure and meaning, never the data itself. Everything runs inside your own environment.

    Use cases

    Where teams put context to work

    Pick the problem you're solving first.

    The Platform

    Where insights land. Where you stay in control.

    The platform is the workbench for your data team and power users. Metagem surfaces the findings, you remediate, then sync the context to catalogs, BI tools, and Copilots.

    See it in a 20-min walkthrough

    Production Cost

    98%Operations

    Active Customer

    95%Sales

    Overall Equipment Effectiveness

    94%Operations
    InsightsToday
    5 reporting conflicts
    12 DQ gaps prioritised
    3 semantic overlaps
    4 awaiting review

    Where it fits

    One context layer, every system and agent

    Systems feed the engine. The engine builds the context layer.
    The context layer powers what your business runs on.

    Read the guide to the context layerSemantic layer vs context layer, comparedHow Graph-RAG retrieves grounded answers

    Context Glossary

    Data Quality Findings

    MCP

    Contextual genAI/BI chat

    MCP

    Agentic Automation

    03 · Propagate

    To every consumer that needs it

    Customer graph
    Finance graph
    Cust. support graph

    Enterprise Context Graph

    Meaning
    Logic
    Mapping

    02 · Build and validate

    Scored by AI, approved by experts

    Context EngineMetagem

    Systems of Record

    SAP
    Salesforce

    Systems of Data

    Microsoft Fabric
    Power BI
    Tableau

    Systems of Knowledge

    SharePoint
    Confluence

    01 · Extract

    Context from your existing sources

    Frequently Asked Questions

    No enterprise we've opened had a clean, current catalog. If your systems were already documented, mapped, and agreed on, you wouldn't need us — that documentation is the deliverable, not the entry ticket. We connect to your systems in whatever state they're in, read the metadata automatically, and hand you the map. Your team only weighs in on the critical 10% that actually moves the business.

    An engine that builds, aligns and propagates context across your data & AI landscape. Metagem stitches context from every source — systems, documents, models, dashboards — into a single live map, shows you exactly where definitions, metrics and meaning misalign, and — once your experts have validated the right meaning — pushes the agreed fixes back out to every consumer that depends on them. You get this through Context Agents (the automations doing the work) and the Context Platform (where your team explores, validates and signs off on the results, with a human in the loop on every meaningful decision). The sovereign AI context layer accumulates as a by-product.

    We treat every tool as either a source or a destination of context. Metagem keeps your data landscape in sync, applies data quality checks where possible, and ensures the most accurate context flows across the systems that need it — without replacing what you already have.

    No. Metagem is read-only and is deployed and managed inside your own private cloud. Your data, and documents never leave your perimeter. A managed SaaS option is available for teams that prefer it, with the same capability set.

    Every piece of context Metagem produces carries source attribution, lineage, and a human validation record. When a regulator or auditor asks where data came from, who approved it, and how AI is using it, you have the answer in one place. Metagem's agents also map data flows against EU AI Act, GDPR, NIS2 and EU Data Act requirements and flag gaps before they become audit findings, with a human in the loop on every AI decision, which is what these regulations actually require.

    Let's see your mess

    We map it and show the ROI.

    Then you decide whether to scale.