The MergeOn Platform
The enterprise foundation for building, governing and operating AI at scale.
Explore the platform →THEMIS Mission Control NewUnderstand what is changing across your organization and bring the right decisions to the right people at the right time.
Runtime Digital Twin PreviewVisualize every runtime, capability and relationship across your AI operating environment.
Create governed AI activity once, with its knowledge, controls, approvals and execution requirements.
Runtime CenterOperate and observe governed Runtimes, activity, execution, evidence and readiness from one operational surface.
Governed KnowledgeTurn enterprise information into structured, governed context that AI can use without losing source meaning and relationships.
Policy & ProtectionDefine the controls that govern what AI may access, what it may do, what must be protected and when a person must approve.
Data ProtectionProtect sensitive values while preserving the business context AI needs to perform the governed task.
Human ApprovalRequire human authority where governed AI activity should not proceed on AI authority alone.
Golden ThreadReconstruct governed AI execution from request to outcome with connected execution evidence.
AI Evaluation & AssuranceVerify what can be proven, evaluate AI behaviour and establish evidence-backed readiness in context.
AI Model GovernanceGovern which models may participate, where they may be used, what evidence supports them and when their qualification must be reconsidered.
Why MergeOn
Turn the knowledge you already have into governed context AI can use.
Policies, procedures, manuals, regulations and operating documents were written for people — not AI.
MergeOn Document Intelligence transforms them into structured Tier-3 Review Packs, preserving meaning, relationships, dependencies and source context. Accepted knowledge can then be governed in the Knowledge Center and supplied to AI at execution.
Better context. Less repeated processing. More efficient AI execution.
Explore Governed Knowledge →Wherever critical knowledge, policy and AI execution have to work together.
Govern policies, controls, product rules and regulated decisions while keeping AI execution traceable.
Healthcare & Life SciencesTurn clinical, operational and regulatory knowledge into governed context while protecting sensitive information.
Logistics & Supply ChainStructure customs, trade, food, agriculture, transport and supplier requirements so AI can work from the right rules for the activity.
Legal & Professional ServicesTransform contracts, precedents, policies and matter knowledge into governed context with source-level evidence.
Industrial & Critical OperationsGovern procedures, technical documentation, safety requirements and operational knowledge across complex environments.
Public Sector & Defense Supply ChainControl how sensitive policy, procurement, compliance and operational knowledge participates in AI-enabled activity.
Build on MergeOn
The application asks for a business outcome. The Runtime governs how it is produced.
An integration calls a published Business Capability rather than a model endpoint, so knowledge, policy, protection, human authority and evidence stay part of the activity instead of becoming your problem to rebuild.
Everything below describes the contract you build against and the architecture behind it.
Explore the developer platform →Everything you need to integrate, extend and build on the MergeOn platform.
API ReferenceComplete REST APIs, authentication, schemas and integration endpoints.
SDKs & ExamplesAccelerate development with SDKs, sample applications and reference implementations.
Technical documentation covering platform architecture, configuration and deployment.
Integration GuidesStep by step guides for connecting AI providers, enterprise systems and business applications.
Architecture PatternsReference architectures and implementation patterns for enterprise AI deployments.
Know where you stand
Most organizations do not have an AI problem. They have a clarity problem.
Before deciding what to build, it helps to establish what your organization already believes about ownership, governance and decision-making — and where those beliefs disagree with each other.
Start with an honest read of where you are. Everything else follows from it.
Start the free benchmark →Take the free 12-question benchmark and get an immediate view of your organization’s AI readiness.
Start the benchmark Leadership Alignment AssessmentCompare leadership perspectives to reveal where your team is aligned, where views diverge and where that difference matters.
Explore the assessmentMergeOn was created to give organizations a governed foundation solid enough to put real AI-enabled work on.
Read our story →Why MergeOn exists and how we are building the enterprise control plane for governed AI execution.
CareersJoin the team building the control plane for governed enterprise AI.
Contact UsTalk to MergeOn about your organization, implementation or enterprise AI programme.
See how the models, cloud, data and enterprise technologies organizations already use can participate in governed MergeOn execution.
Implementation PartnersBuild a governed AI practice on MergeOn and help enterprises move from AI pilots into controlled production.
Become a MergeOn Implementation PartnerBring MergeOn into client engagements, build repeatable governed AI capability and register for partner enablement and future certification.
Govern the model.
Not just the application using it.
Enterprise AI depends on models that change, providers that change and operating contexts that change. MergeOn keeps the model, its qualification, permitted use and governing evidence connected to the activity in which it participates.
Know the model. Know where it may operate. Know what evidence supports it.
Model
Model identityQualification
Evidence availablePermitted use
Governed contextChange
Current stateA model should not become trusted just because somebody connected an API.
Using a model and governing a model are different things. Enterprise teams need to know what model is participating, which provider or deployment it belongs to, what is known about it, what evidence has been established and the governed contexts in which it is permitted to operate.
MergeOn keeps that model context connected to governed AI activity rather than leaving it scattered across applications, configuration files and review documents.
Identify
Know which model or model version is being governed.
Qualify
Associate the evaluation and assurance evidence relevant to its intended use.
Admit
Determine whether it may participate in a governed context.
Observe
Retain the relationship between the model, its use and the evidence produced around it.
Change the model. Keep the governed operation.
The model is not the operating system.
MergeOn keeps the business activity, knowledge, policy, protection, authority and execution controls outside the model. The model participates within that governed context.
That means teams can qualify a different model, change the model used by an activity and retain the governed structure around it — rather than rebuilding the application around a new provider.
Governed operation
Model
The model can change. The governed operation remains.
Provider
Where the model or AI service comes from.
Model
The governed model or model context participating in the activity.
Governance
The controls, qualification and evidence associated with its permitted use.
Swap without rebuilding. Re-qualify without starting again.
Plenty of platforms can call several model APIs. That is not the same as keeping the enterprise control structure out of whichever model happens to be selected.
The governed operation stays put. The new model, however, is a new probabilistic participant — so its qualification and evidence position still has to establish whether it is suitable for that particular activity.
Make the operating system deterministic around a probabilistic model.
Govern the operation independently of the model
Knowledge, policy, protection, authority and execution remain controlled by MergeOn.
Qualify models for a specific use
AI Evaluation & Assurance establishes evidence about how the model performs in that governed context.
Record that position in AI Passport
Identity, version, qualification, permitted use and supporting evidence travel with the governed model.
Change models without rebuilding the operation
A different model can be introduced into the same governed activity and evaluated against the same operating requirements.
Know exactly what actually ran
Golden Thread retains the model and governed execution context associated with the operation.
Give every governed model an assurance record that can travel with it.
A model name is not enough. Its governance position depends on more than who supplied it. Teams need the relevant identity, version, qualification, evaluation, permitted-use and evidence context available when deciding whether that model is appropriate for a governed activity.
AI Passport is MergeOn’s assurance record for a governed model: the context that allows a model’s use to be examined against what is actually known about it.
The question is not “Is this a good model?” It is “Is this model suitable here?”
The same model may be appropriate for one governed activity and inappropriate for another. Its use can depend on the business capability, environment, release, policy, protection requirements, human authority and evaluation evidence surrounding the activity.
Model governance therefore belongs to the operating context — not to a static approved-model spreadsheet.
Qualification is meaningful when it is attached to the context in which the model will actually operate.
Evaluation should change what you know about the model.
AI Evaluation & Assurance establishes evidence about behaviour, performance and the conditions being evaluated. AI Model Governance connects that evidence to the model and the governed context in which teams intend to use it.
A benchmark can describe a model in general. Governed evaluation can help establish whether that model is suitable for the specific activity being considered.
Evaluate
Measure the behaviour or condition that matters to the governed activity.
Associate
Keep the result connected to the model and context it was produced against.
Govern
Use the available evidence when determining the model's governed position.
A new model version is new evidence territory.
Models change. Providers change them. Configurations change. The activity around them changes. Evidence established for one model, version or operating context should not silently become evidence for another.
MergeOn keeps the governed model context explicit so teams can determine when previous qualification still answers the question — and when further evaluation or assurance is required.
Established state
The model and context against which the current evidence was produced.
Change
The model, version, provider, configuration or relevant operating context changes.
Review
Determine whether the existing evidence still answers the governance question.
New evidence
Where required, further evaluation establishes the position under the changed context.
Know which model actually participated.
Model governance matters most when it remains connected to real governed activity. The model context associated with an execution can form part of the evidence needed to understand what operated, under which controls, against which qualification context and with what outcome.
AI Model Governance
Establish the governed model context and supporting assurance.
Runtime
Execute the governed activity with its applicable operating context.
Golden Thread
Connect the model and governing context to execution evidence where recorded.
A model’s governance position should not end with approval.
Individual evaluations establish evidence at a point in context. Governed execution produces further evidence about how AI is operating. Where that evidence is available, ATHENA can reason across evaluation and execution evidence to help surface patterns, changes and areas requiring investigation.
AI Evaluation & Assurance
Evidence about behaviour.
AI Model Governance
Governed model context.
ATHENA
Intelligence across available evidence.
Know it. Qualify it. Govern it. Evidence it.
AI Evaluation & Assurance
Establish evidence about behaviour and suitability in context.
AI Model Governance
Govern the model, its qualification and permitted-use context.
Golden Thread
Connect the model and governing context to what actually executed.
ATHENA
Reason over available model, evaluation and execution evidence.
Move past the pilot.
Put your first governed AI activity into production.