Intelligence should
start with the person.
AiX is the Experience Operating System for Enterprise AI — designed to turn human intent into governed intelligent action across agents, models and enterprise systems.
Instead of forcing people to navigate disconnected prompts, applications and AI tools, AiX brings intelligence together around what the user is trying to accomplish — creating one coherent, contextual and controlled experience.
Enterprise AI has an experience problem.
Enterprises are investing in models, copilots, agent frameworks, automation engines and AI platforms.
The intelligence is becoming more powerful.
The experience is not.
Users are still moving between applications, prompts, workflows and disconnected AI interfaces — often with little visibility into what agents are doing, what information they are using or what actions they are taking.
The result is a growing AI estate without a coherent way for people to understand, direct and trust the intelligence around them.
AiX changes where the design starts
The experience defines what intelligence, context and orchestration are required — not the other way around.
What is this person trying to accomplish?
That is where AiX begins.
We design how intelligence enters the enterprise.
AiX sits between people and the enterprise AI estate, creating the experience through which users understand, direct, supervise and collaborate with intelligent systems.
It brings together the right interaction context, agents, models, enterprise systems and controls around the outcome the user is trying to achieve.
Determines what intelligence can do.
Determines whether people can understand it, trust it, control it and use it effectively.
Intelligent agents need intelligent interactions.
AiX makes human-agent interaction part of the architecture — designing how intent is expressed, ambiguity is resolved, recommendations are explained, approvals are requested and users remain in control as intelligence moves from insight to action.
From human intent to enterprise action.
AiX works from the outside in.
It starts with what the person is trying to accomplish, then brings together the context, intelligence, systems and controls required to achieve that outcome through one coherent experience.
Experience
Design how people engage with intelligence.
AiX creates the interaction through which users express intent, receive guidance, understand progress, review recommendations, provide approvals and stay in control.
The experience is not a layer added after the intelligence is built. It is part of how the intelligence is designed.
AiX supports experiences across conversational interfaces, portals, mobile applications, operational consoles, collaboration channels and embedded enterprise applications.
The question AiX asks
What should this person experience at this moment?
Interaction Context
Understand the person, the intent and the moment.
AI needs more than data context.
AiX assembles the context surrounding the interaction — who the user is, the role they are performing, what they are trying to achieve, where they are in the journey, what authority they have and what enterprise information is relevant to the task.
That context can include identity, permissions, policies, approval thresholds, business rules, conversation state and information drawn from enterprise systems.
Not only
What do we know?
But also
Who is asking? Why are they asking? What are they allowed to do?
Experience Orchestration
Coordinate intelligence around the user journey.
Behind a single intelligent experience may sit multiple agents, models, tools, workflows and enterprise systems.
AiX coordinates how those capabilities participate in the interaction — when intelligence is invoked, when clarification is required, when a specialist capability is needed, when approval must be requested and how results are brought back into one coherent experience.
Backend orchestration focuses on
What executes next?
AiX Experience Orchestration focuses on
What should the user experience next?
Even when multiple agents participate, users should experience one coordinated intelligent service rather than the complexity underneath it.
Governance
Govern the relationship between people and intelligence.
As AI moves from recommendation toward action, control becomes part of the experience itself.
AiX applies identity, permissions, policies, approvals, auditability, human oversight and intervention throughout the interaction.
It makes explicit:
- what the AI can do independently;
- what it may recommend;
- what requires approval;
- what must remain human-controlled;
- and when the system must escalate.
This makes autonomy a governed design decision rather than a technical switch.
Enterprise Action
Turn intelligence into outcomes.
AiX does not stop at answers and recommendations.
It connects intelligent experiences to the applications, APIs, workflows, data and operational platforms the enterprise already uses so that approved intent can become action.
The underlying systems remain systems of record and execution. AiX creates the intelligent experience through which people engage with them.
One experience. Many sources of intelligence.
The user does not need to know which model answered the question, which agent performed the analysis, which workflow coordinated the task or which enterprise system executed the action.
AiX manages the experience above that complexity.
The intelligence can change.
The experience remains coherent.
Built as software. Designed as an operating layer.
AiX is not a methodology wrapped around partner technologies.
It is enterprise software composed of reusable runtime services, APIs, SDKs, libraries and deployment capabilities that provide a consistent operating layer for intelligent experiences.
The platform brings together six core capabilities
AiX Experience Layer
Where people meet intelligence.
The Experience Layer is the human- and channel-facing expression of AiX.
It defines how users express intent, collaborate with agents, understand progress, review recommendations, approve actions, intervene when necessary and move from insight to outcome.
It supports intelligent experiences across portals, applications, conversational channels, mobile interfaces, operational consoles and embedded enterprise environments.
Purpose
Create one coherent, trusted relationship between people and enterprise intelligence.
AiX Studio
Compose intelligent experiences.
AiX Studio is the environment for designing, building and extending experiences on the platform.
It brings together reusable interaction patterns, agentic UI components, experience templates, workflows, APIs, SDKs and low-code or prompt-driven composition capabilities.
The goal is not to make every experience dependent on bespoke development. Over time, customers and partners can use AiX Studio to compose and extend their own intelligent experiences on top of the AiX operating layer.
Purpose
Turn experience design into a reusable enterprise capability.
Agentic Runtime & Harness
Support intelligent behavior over time.
The Agentic Runtime provides the execution capabilities required to support agent behavior across complex, long-running interactions.
It manages context, state, memory, multi-agent coordination, pausing and resuming, and human intervention as interactions evolve.
The Harness also embeds reusable interaction behaviors such as clarification, progress communication, approvals, escalation, recovery and intervention.
Purpose
Give intelligent experiences continuity, state and controlled behavior.
Agent Gateway
Connect AiX to the enterprise AI estate.
The Agent Gateway provides the governed connection point between AiX and the capabilities that sit beneath or around it. That can include:
The Gateway allows AiX to participate in a heterogeneous enterprise architecture without forcing the organization to replace the technologies it already uses.
Purpose
Make diverse intelligence accessible through one governed operating layer.
AiX Core Services
Translate the enterprise for intelligence.
Enterprise context is fragmented across identity systems, security platforms, policies, organizational structures, approval rules, applications and data.
AiX Core Services abstract and translate those capabilities into reusable operating services for identity, authorization, policy, governance, trust, context, evaluation and common enterprise behaviors.
This is how AiX helps agents understand not only enterprise data, but the conditions under which that information may be used and acted upon.
Purpose
Turn fragmented enterprise controls and context into agent-ready operating services.
AiX Control Plane
Govern and observe the intelligent experience.
The Control Plane gives organizations operational visibility and control across the AiX environment. It provides capabilities for:
But AiX goes beyond observing technical execution. It can also examine the quality of human-agent interaction through signals such as task completion, abandonment, clarification frequency, correction, approvals, escalation, intervention and outcome satisfaction.
We observe not only whether the agent ran.
We observe whether the interaction worked.
Purpose
Make intelligent experiences measurable, governable and continuously improvable.
One operating layer. An open AI estate.
AiX does not require the enterprise to standardize on one model, one agent platform or one application stack. It is designed to sit across a heterogeneous environment of enterprise systems, models, agent platforms, data sources and specialist technologies.
Experience Layer
How people engage.
Studio
How experiences are composed.
Runtime & Harness
How intelligent interactions behave.
Gateway + Core Services
How intelligence connects to enterprise capabilities and controls.
Control Plane
How the environment is governed, observed and improved.
AiX creates coherence above the complexity.
Enterprise AI will never be one platform.
Organizations will use different models, agent frameworks, enterprise applications, data platforms and specialist AI systems.
That is not a problem to eliminate. It is the reality AiX is designed for.
AiX creates a consistent experience and operating layer across that heterogeneous estate — allowing enterprises to adopt the intelligence they need without forcing users to navigate the complexity underneath it.
The intelligence can come from anywhere.
The experience should still feel like one enterprise.
AiX does not replace the stack
It brings the stack together around the person and the outcome they are trying to achieve.
AI Models & Agent Platforms
Provide reasoning, retrieval, agent execution, specialized skills and backend orchestration.
AiX can consume those capabilities through governed interfaces and bring them into a consistent user experience.
Examples
Domain Intelligence Platforms
Provide deep intelligence for specific operational or business domains.
AiX can surface that intelligence as part of a broader enterprise interaction, combining it with other agents, systems and context when the user journey requires it.
Examples
Enterprise Systems
Remain the systems of record and systems of action.
ERP, CRM, ITSM, finance, HR, productivity, identity and operational platforms continue to execute the processes the enterprise depends on. AiX provides the intelligent experience through which users and agents can engage with those systems.
Data, Knowledge & Identity
Provide the enterprise context required for safe and relevant intelligence.
AiX brings these sources into the interaction while preserving enterprise permissions, policies and authority.
Where AiX sits
People & Channels
AiX
AI & Agent Platforms
Domain Platforms
Enterprise Estate
AiX creates coherence above the complexity. It gives the enterprise a stable experience layer even as the technologies underneath it evolve.
The user should not have to relearn the enterprise every time the intelligence stack changes.
Cohere + AiX
Powerful agent intelligence. Designed around the person.
Cohere can provide enterprise-grade model, retrieval, agent execution and backend orchestration capabilities.
AiX complements those capabilities by focusing on the interaction above them:
- Who is the user?
- What are they trying to accomplish?
- What context is required?
- What authority do they have?
- When should intelligence ask, recommend or act?
- How should the outcome be presented?
AiX Experience Orchestration coordinates how those capabilities participate in the user journey.
Cohere can orchestrate how agents execute.
AiX orchestrates how that intelligence is experienced.
Meridian + AiX
Domain intelligence becomes part of the enterprise experience.
Meridian brings AI-native capabilities across AIOps, IT Service Management and Observability.
AiX can bring that specialist operational intelligence into broader user journeys — combining Meridian insight with enterprise context, other agents and systems of action.
A CIO, service owner or operator should not need to understand which platform produced each element of the answer.
They should experience
one question → one coherent investigation → one governed path to action.
Built for partners
AiX is designed not only to consume partner capabilities, but to give technology providers a consistent way to bring their intelligence into enterprise experiences.
Partners can contribute
AiX provides the experience and governance layer around them.
Better intelligence underneath.
Better experience above.
Autonomy should be designed, not assumed.
Agentic AI introduces a new question into enterprise system design: how much authority should intelligence have — and under what conditions?
AiX treats autonomy as a governed interaction decision. The right level of autonomy depends on the user, the task, the risk, the confidence of the system and the controls the enterprise requires.
The autonomy continuum
Assist
The AI helps the user understand, research or complete a task.
The human remains fully in control.
The goal is not maximum autonomy.
The goal is appropriate autonomy.
A low-risk, repetitive interaction may justify a high degree of autonomous action.
A financial approval, sensitive citizen service, privileged infrastructure change or material business decision may require human review regardless of how capable the underlying AI becomes.
AiX allows autonomy to be calibrated around the context of the interaction rather than applied uniformly across the enterprise.
Human control is part of the experience
Governance cannot exist only in backend policy engines. People need to understand what intelligence is doing and have meaningful ways to influence its behavior.
AiX interaction patterns can provide users with the ability to
Approve
Authorize a proposed action.
Edit
Modify the recommendation or action before execution.
Reject
Prevent an action from proceeding.
Pause
Temporarily stop execution.
Redirect
Change the objective or provide new information.
Cancel
Terminate the activity.
Escalate
Transfer responsibility to another person or process.
Retry
Re-run an activity after correction or additional context.
Intervene
Take control when circumstances require it.
Users should never have to wonder
“What is the AI doing, and how do I stop it?”
Trust requires visibility
Autonomy becomes useful only when people understand enough about what the system is doing to trust it appropriately. AiX experiences can expose the information required for that trust without overwhelming the user with technical complexity.
Depending on the interaction, AiX can communicate
What the system understood
The intent it believes the user expressed.
What it is doing
The current activity and progress.
What information it used
Relevant sources, systems and evidence.
Why it is recommending an action
The operational explanation behind the result.
How confident it is
Uncertainty, assumptions or conditions that may affect the outcome.
What it intends to do next
Before consequential actions are taken.
How the user can intervene
The controls available at that moment.
Different users. Different levels of control.
The same intelligent capability may behave differently depending on who is interacting with it.
AiX can use Interaction Context to understand
Identity
Who is making the request?
Role
In what capacity are they acting?
Authority
What decisions or actions can they authorize?
Policy
Which rules apply?
Risk
What is the potential impact of the action?
Journey State
Where is the user in the process?
Confidence
How certain is the intelligence about the recommendation or action?
The level of autonomy can then adapt to the situation.
Governance that travels with the interaction
Traditional controls are often attached to individual systems. Agentic experiences can span many.
AiX carries governance through the interaction as intelligence moves across agents, applications, data and systems of action.
This creates a continuous control model from human intent through enterprise execution.
Autonomy is not the absence of human control.
It is human control designed into the system.
AiX makes it possible for enterprises to increase the capability of intelligent systems without losing visibility, accountability or authority over how those systems behave.
It is not enough to know that the agent ran.
Traditional observability tells you whether systems are available, performant and behaving as expected.
Agentic AI introduces another question
Did the interaction actually work?
AiX extends observability into the human-agent experience — measuring not only technical execution, but whether users understood the intelligence, trusted it, completed the task and achieved the intended outcome.
From system health to experience health
A technically successful agent run can still produce a poor enterprise experience.
And the user may still abandon the task, reject the recommendation, escalate to a human or lose confidence in the system. AiX makes those interaction signals visible.
AiX can observe
Task completion
Did the user accomplish what they set out to do?
Abandonment
Where did the user stop or disengage?
Clarification frequency
How often did the AI fail to understand the intent the first time?
Correction frequency
How often did users need to fix or redirect the system?
Approval & rejection
Which recommendations or actions are being accepted — and which are not?
Escalation
When and why is the interaction being handed back to people?
Intervention
How often do users need to pause, redirect or stop execution?
Trust & confidence
Do users understand and trust the recommendations they are receiving?
Time saved
Is the intelligent experience materially reducing effort?
Adoption
Are people actually choosing to use it?
Outcome satisfaction
Did the interaction create the intended result?
Observe the interaction, not just the infrastructure.
Experience Observability gives product owners, AI teams, risk leaders and operations teams a common view of how intelligent experiences are performing. It connects technical behavior with human behavior.
Organizations can ask questions such as
- Where are users losing confidence?
- Which agent interactions require the most correction?
- Where are approval rates unusually low?
- Which experiences produce the most escalations?
- Are higher levels of autonomy improving outcomes — or increasing intervention?
- Where is AI creating measurable value for the user?
Different audiences. Different views.
The same interaction can be understood at different levels.
Executive
Is the experience delivering value?
Outcome · Adoption · Time saved · Satisfaction · Business impact
Product & Experience
Are people able to use it effectively?
Completion · Abandonment · Clarification · Correction · Trust
Risk & Governance
Is intelligence behaving within policy?
Approvals · Rejections · Escalations · Intervention · Audit
Engineering & Operations
Is the underlying system performing correctly?
Agent activity · Model behavior · Tool calls · Dependencies · Errors · Latency
This follows the principle of progressive disclosure already built into the AiX experience model: different users can inspect the same interaction at the level of detail relevant to them.
From observability to improvement
Experience telemetry is not only for reporting. It becomes part of how AiX evolves.
Interaction data can be used to refine
Intent design
Where users struggle to express what they need.
Interaction patterns
How information, recommendations and actions are presented.
Autonomy levels
Where the system should assist, recommend, ask or act.
Agent behavior
Where clarification, escalation or recovery needs improvement.
Policies & controls
Where governance creates unnecessary friction — or insufficient protection.
Experience design
Where the user journey can become simpler, faster or more trusted.
The result is a continuous feedback loop
We observe not only whether the agent ran.
We observe whether the interaction worked.
That is the difference between operating AI infrastructure and operating an intelligent enterprise experience.
Start with the outcome, not the application.
AiX is designed for journeys that cross systems, teams, channels and sources of intelligence.
Instead of asking users to understand which application, agent or workflow they need, AiX begins with what they are trying to accomplish — then brings the right context, intelligence and actions together around that intent.
The result is not another chatbot.
It is an intelligent experience.
Government & Citizen Services
From navigating services to achieving outcomes.
Citizens should not need to understand government structures, application boundaries or internal workflows to get something done.
AiX can create intelligent experiences that understand intent, guide users through complex service journeys, coordinate information across agencies and systems, and introduce approvals or human intervention where needed.
Example experiences
“Help me understand which permits I need to open this business.”
AiX can clarify intent, gather context, identify relevant requirements, coordinate specialist intelligence and guide the user through the journey.
“What is happening with my case?”
AiX can bring together case status, policy, supporting documents and relevant actions into one contextual experience.
“I need to update my circumstances across government services.”
The experience can coordinate across multiple systems rather than forcing the citizen to repeat the same journey in each application.
Potential areas
Executive & Decision Intelligence
Ask the enterprise, not the dashboard.
Executives often need answers that span operational, financial and business systems.
AiX can provide an interaction layer through which leaders express an objective or question while the underlying intelligence gathers relevant evidence, coordinates specialist capabilities and presents a coherent path from insight to action.
“Why has service performance deteriorated this month, what is driving it, and what should we do?”
The experience could combine
- Operational intelligence from platforms such as Meridian or Observability systems
- Business context from enterprise applications and data
- Specialist agents for analysis and investigation
- Enterprise policies governing available actions
- Approvals and systems of action required to execute the response
The executive experiences one investigation, not the technology stack underneath it.
IT & Digital Operations
From detecting problems to coordinating resolution.
Modern operations teams work across Observability, ITSM, infrastructure, cloud, security and application platforms.
AiX can create operational experiences that bring those systems together around the intent of the operator.
“Investigate the degradation affecting our citizen-services platform.”
AiX can coordinate the experience while specialist platforms and agents perform the underlying work:
Detect
Bring together relevant service and operational signals.
Investigate
Coordinate specialist analysis across Observability, AIOps and enterprise knowledge.
Explain
Present likely causes, supporting evidence and uncertainty.
Recommend
Propose remediation based on context and policy.
Approve
Introduce human authorization where required.
Act
Trigger the appropriate systems of action.
Observe
Track the outcome and continue the interaction if the issue persists.
Enterprise Knowledge
Turn knowledge into action.
Enterprise knowledge is rarely contained in one repository.
It exists across documents, policies, applications, databases, communications and the experience of people across the organization.
AiX can bring relevant knowledge into the context of the user’s objective — without making the user search every underlying source independently.
“Can I approve this purchase?”
Rather than returning a policy document, an AiX experience can understand:
- who the user is;
- what role they are performing;
- the value and nature of the purchase;
- their delegated authority;
- the applicable policy;
- the required approvals;
- and the next available action.
The experience moves from finding information to helping the person accomplish the task.
Employee Experience
Replace application journeys with intent-driven journeys.
Employees navigate dozens of enterprise systems simply to perform everyday work. AiX can create an intelligent experience above those systems.
Instead of
the employee can begin with:
“I am relocating to another office. What do I need to do?”
AiX can interpret the intent and coordinate the relevant enterprise capabilities around the journey.
The user experiences the outcome. The enterprise systems continue doing what they were designed to do underneath it.
Potential experiences
Customer & Service Experience
One relationship, many systems.
Customer journeys frequently span CRM, service management, billing, knowledge, fulfillment and other applications.
AiX allows the interaction to remain coherent while intelligence and actions move across those systems.
The experience can retain context, coordinate specialist agents, surface relevant information, introduce human handoffs and maintain continuity across channels.
A conversation can begin in a portal, continue through a collaboration channel or contact center, and still retain the interaction context required to move the outcome forward.
Complex Business Operations
Give people outcomes instead of workflows.
Many business processes do not really follow the neat sequence represented inside enterprise applications.
People interpret information, consult colleagues, make judgments, apply policies, obtain approvals and move between systems before reaching an outcome. The real journey is the work people are trying to accomplish — the enterprise system represents only part of it.
AiX can create an intelligent layer around these complex journeys.
Potential areas
The common pattern
Different use cases. The same AiX principle.
Human Intent
What is the person trying to achieve?
Interaction Context
Who are they, what role are they performing, and what enterprise context matters?
Experience Orchestration
Which intelligence, agents, systems and decisions need to participate?
Governance
What can be recommended, approved or executed?
Enterprise Action
How does the interaction move from intelligence to outcome?
AiX hides the complexity without removing the control.
Not every experience needs a new agent
AiX is not based on the assumption that every enterprise problem requires another autonomous agent.
An experience may use
- existing enterprise applications;
- a specialized AI platform;
- one agent;
- multiple agents;
- traditional workflows;
- human expertise;
- or a combination of them.
What matters is not how many AI components sit underneath. What matters is whether the person can accomplish the outcome intelligently, safely and intuitively.
That is the experience AiX is designed to create.
Intelligence on your terms.
Enterprise AI does not have a single deployment model.
For governments, regulated industries and mission-critical organizations, the architecture must reflect requirements for data residency, security, control, performance and operational assurance.
AiX is designed to support that reality.
On-prem first. Deployment flexible.
AiX can be deployed in environments where sensitive data, agent execution, enterprise context and governance services must remain under the organization’s control. That includes:
On-premises environments
For organizations that require infrastructure, data and AI services to remain within enterprise-controlled facilities.
Sovereign cloud environments
For regulated workloads that must remain within approved jurisdictions and operating boundaries.
Private and hybrid architectures
Where enterprise systems, models and AI services span different environments but must still participate in one governed experience.
Selected cloud AI services
Where policy and risk allow external AI capabilities to be introduced without compromising the control model.
Architecture should follow policy — not force policy to follow architecture.
Keep enterprise control where it matters
AiX is designed so organizations can make deliberate choices about where intelligence runs, what information leaves an environment and which services are permitted to participate in an interaction.
Controls can be applied around
Data
What information can be accessed, transmitted or retained.
Models
Which models are approved for specific classes of workload.
Agents
Which agents can participate and what authority they are given.
Tools & Systems
Which enterprise resources intelligence can access or act upon.
Identity
Which user, role and authority context governs the interaction.
Audit
What must be recorded for security, compliance and accountability.
Action
Which activities may remain autonomous and which require human approval.
Sovereignty is more than data location
Keeping data inside a boundary is important.
But enterprise AI sovereignty also requires control over how intelligence behaves.
AiX extends the idea of sovereignty across the complete interaction
- Where does the data reside?
- Which model is allowed to process it?
- Which agent can use it?
- What does that agent know about the user?
- What actions can it perform?
- Which policies govern those actions?
- When must a human remain involved?
- Can every consequential interaction be audited?
Sovereign infrastructure without sovereign control is incomplete.
One experience across hybrid intelligence
A single AiX experience does not require every capability to run in the same environment. An enterprise may combine:
- on-premises models;
- private knowledge stores;
- sovereign AI services;
- approved cloud models;
- partner agent platforms;
- legacy enterprise applications;
- and modern SaaS services.
AiX provides the interaction and governance layer across those environments.
The user experiences one intelligent service. The enterprise retains control over which capabilities participate and under what conditions.
Built for government & regulated enterprise
For these organizations, considerations such as sovereignty, security, explainability, auditability and human oversight are not optional design features. They are architectural requirements.
AiX is designed for environments where enterprise AI must operate within those boundaries from the beginning — rather than being adapted for them after the fact.
Government
Citizen services · Shared services · Policy-driven interactions · Sovereign AI
Financial Services
Controlled decision support · Sensitive data · Approval-driven actions · Auditability
Energy & Utilities
Mission-critical operations · Operational resilience · Controlled automation
Transportation & Critical Infrastructure
High-availability environments · Operational intelligence · Governed intervention
Open to intelligence. Closed to uncontrolled risk.
AiX allows enterprises to use the models, agents and platforms appropriate to each use case while preserving a consistent experience, governance model and operating boundary.
From intelligent idea to operating experience.
AiX is the platform.
The AiX Foundry is how we design, build, validate and industrialize the intelligent experiences that run on it.
It brings together agent engineering, experience design, architecture, governance, integration and observability into one delivery model.
The goal is not simply to build an agent. The goal is to create an intelligent experience that people can use, trust and operate in the real enterprise.
Two disciplines. One outcome.
The Foundry combines two complementary engineering disciplines — the Agent Engineering Studio and the Agentic Experience Studio.
Agent Engineering
Design the intelligence behind the experience.
Models
Select and configure the appropriate models.
Knowledge
Connect enterprise information and retrieval.
Tools
Define what capabilities agents can use.
Workflows
Coordinate backend execution and system actions.
Evaluation
Test quality, reliability and task performance.
Deployment
Prepare agent capabilities for production operation.
Agentic Experience Engineering
Design the relationship between people and intelligence.
User & role research
Understand who is interacting with the system and what they are trying to achieve.
Journey design
Map how the person moves from intent to outcome.
Interaction design
Define how intent, clarification, recommendations and actions are expressed.
Trust & control patterns
Design approvals, explanations, uncertainty, intervention and escalation.
Experience prototyping
Test how intelligent interactions behave before industrializing them.
Adoption & usability evaluation
Measure whether people can understand, trust and use the experience effectively.
We engineer both the intelligence and the relationship people have with it.
The AiX delivery lifecycle
Frame the outcome
What is the person trying to accomplish?
Define the user, business outcome, value case and operating problem before selecting the technology.
We identify where intelligence can materially improve the journey and where it should not.
Design the experience
What should the ideal interaction look like?
Map the journey from human intent to enterprise outcome.
Define how users express intent, how the system responds, where clarification is required and how the experience moves across channels or roles.
Calibrate autonomy
What should intelligence be allowed to do?
Determine whether the AI should:
Autonomy is designed around risk, confidence, authority and business context.
Architect the intelligence
What capabilities need to sit behind the experience?
Identify the models, agents, knowledge, enterprise systems, APIs, workflows and specialist platforms required to fulfill the journey.
This is where technologies such as Cohere, Meridian or existing customer platforms can be introduced when they are the right capability for the outcome.
Engineer the interaction
How should people and agents work together?
Design interaction context, dialogue state, clarification, progress communication, approvals, explainability, intervention and recovery.
The AiX interaction model treats clarification, confidence, consent, explainability and intervention as part of agent behavior.
Connect & govern
How does intelligence safely engage with the enterprise?
Connect agents and experiences to identity, applications, data, tools and systems of action through governed interfaces.
Establish
Governance is designed into the interaction before production.
Validate the experience
Does it work technically — and does it work for people?
Evaluate both sides of the system.
Technical validation
Accuracy · security · resilience · performance · integration · agent behavior
Experience validation
Understanding · usability · trust · clarification · intervention · completion · outcome quality
A technically successful agent is not enough if users cannot rely on the experience.
Deploy & operate
Can the experience perform in the real enterprise?
Deploy AiX and the supporting capabilities into the agreed on-premises, sovereign, hybrid or cloud architecture.
Then continuously observe, govern and improve the experience through the AiX Control Plane and YourCompass managed operations.
Experience design is not a front-end phase
It is a discipline that runs through the entire lifecycle.
It influences
Architecture
Because the experience determines what context and intelligence are required.
Agent behavior
Because agents need interaction patterns for clarification, approval and recovery.
Governance
Because trust, consent and control must be visible to users.
Observability
Because success includes what happened to the person, not just what happened in the runtime.
Operations
Because real-world interaction telemetry becomes the feedback loop for improvement.
Interaction Design is both a visible platform layer and a cross-cutting discipline across the operating system.
The AiX Interaction Design Framework
Every AiX engagement can apply six core disciplines:
Frame the relationship
Define the agent's role, authority, boundaries and accountability.
Map the journey
Identify where intelligence assists, recommends, acts, asks for approval or hands control back.
Design the dialogue
Define intent capture, clarification, progress, explanation and recovery.
Calibrate autonomy
Match the level of autonomy to risk, confidence, role and context.
Design for trust & control
Make evidence, permissions, uncertainty, actions and intervention visible.
Measure & improve
Use interaction telemetry, feedback and outcomes to continuously evolve the experience.
Build once. Learn continuously.
AiX allows intelligent experiences to evolve after deployment rather than remain fixed at go-live.
Each interaction generates insight into how the experience can become clearer, safer, more useful and — where appropriate — more autonomous.
The Foundry gets intelligence into production.
Experience Observability makes it better once it gets there.
Because enterprise AI is becoming more powerful — and more fragmented.
Enterprises are adding models, agents, copilots, automation platforms and specialist AI systems at speed.
That increases capability.
It also increases complexity.
Without a common experience and operating layer, users are left navigating different interaction models, permissions, controls, interfaces and workflows across the AI estate.
AiX creates a coherent layer between people and the growing enterprise AI estate — one that starts with human intent, brings together the right context and intelligence, governs how that intelligence behaves, and turns it into enterprise action.
Eight differentiators
Human Intent First
Interaction Intelligence
Interaction Context
Experience Orchestration
Governed Autonomy
Open Ecosystem
Experience Observability
Sovereign by Design
Human intent first
Start with what the person is trying to accomplish.
Most enterprise technology is organized around systems. AiX is organized around outcomes.
Instead of asking users to understand which application, workflow or AI capability they need, AiX starts with the intent and works inward.
Traditional approach
AiX approach
That changes the design question from:
“Where can we add AI?”
to:
“What would the ideal intelligent experience look like for this person?”
Experience is part of the architecture
AI should not end in a prompt box.
Agentic systems change the relationship between people and software.
That means the experience must also determine how ambiguity is resolved, when approval is required, how confidence is communicated and how people remain in control.
AiX makes those interaction decisions part of the architecture itself.
Agent engineering determines what intelligence can do. Interaction intelligence determines whether people can understand, trust and use it.
Coherence without lock-in
One experience across a heterogeneous AI estate.
AiX does not assume that the enterprise will standardize on one model, one agent platform or one technology provider.
It is designed to work with the capabilities organizations already have — and the ones they will adopt next.
The experience does not have to fragment every time the stack evolves.
Governed from intent to action
Governance should travel with the interaction.
Agentic AI increasingly moves beyond information into recommendation, decision and action.
AiX allows the enterprise to design the boundaries of that autonomy around user identity, authority, policy, risk and context.
The objective is not maximum autonomy. It is the appropriate autonomy for the moment.
Observe what people experience
Technical success is not the same as successful AI.
A model can respond correctly. An agent can complete its run. A workflow can execute. And the user can still fail to accomplish the task.
AiX extends observability into the interaction itself — making signals such as completion, correction, approval, escalation, intervention, adoption and outcome satisfaction visible.
We observe not only whether the agent ran.
We observe whether the interaction worked.
Built for the real enterprise
AI has to operate inside the environment that already exists.
Real enterprises contain legacy applications, modern platforms, fragmented data, identity systems, policies, organizational boundaries and operational constraints.
AiX does not require those assets to be replaced. It creates the intelligent experience above them.
That makes AiX particularly suited to environments where:
- enterprise integration matters;
- governance cannot be optional;
- human oversight is required;
- technology estates are heterogeneous;
- sovereignty matters;
- and production operation matters as much as innovation.
AiX is software — not a slideware architecture
Reusable runtime services, APIs, SDKs and libraries.
AiX is not simply a consulting framework, methodology or collection of partner technologies.
It is software built from reusable runtime services, APIs, SDKs, libraries and deployment capabilities that provide the operating foundation for intelligent enterprise experiences.
And because AiX Studio is designed to make experience composition reusable, the objective is not permanent dependence on bespoke implementation.
Customers and partners can increasingly build and extend experiences on the platform themselves.
The AiX difference
Other platforms make AI more capable. AiX makes enterprise AI more usable, coherent and governable.
We design how intelligence enters the enterprise.
AiX turns a fragmented AI estate into a coherent enterprise experience.
Ready to experience AiX?
The future of enterprise AI is not another interface.
It is an intelligent experience.
AiX brings people, enterprise context, agents, models, systems and governance together around what the user is actually trying to accomplish.
One coherent experience that turns human intent into governed enterprise action.
See how AiX brings together human intent, Interaction Context, Experience Orchestration, governed autonomy and enterprise action in one operating environment.
Experience AiXYou do not need to begin with a platform transformation. Begin with an outcome.
Bring us a service journey, business process, operational challenge or enterprise experience that should work differently in the age of AI.
Together, we can determine
- where intelligence creates real value;
- what the ideal experience should become;
- which agents, models and enterprise capabilities should participate;
- what level of autonomy is appropriate;
- and how the experience can be governed, deployed and operated in production.
AiX
The Experience Operating System for Enterprise AI.
We design how intelligence enters the enterprise.
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