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Category · AI agent platform

AI agents that act, with the control your operation demands.

Hypervisor is Karpa AI's platform for putting AI agents to work in your company's systems. They understand the request, involve the right department, carry out the task and record everything, with risk rules and human approval when needed. It does not depend on an industry: the same engine serves any line of business.

Hypervisor AI Agents Platform
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The challenge

Assistants that only answer do not run the operation.

A chatbot answers, but someone still has to resolve the request in some system. Real requests cross departments, need rule-based decisions, and give IT and legal good reason to distrust an AI with free access to systems.

  • Requests that cross departments

    A single customer request often involves several departments and systems. Without coordination, it bounces from queue to queue.

  • AI without brakes

    Giving AI direct access to systems, without limits, verified identity and approval, is a risk no serious operation accepts.

  • Slow change

    Every rule or flow adjustment becomes a development project and a new release, and the operation waits for weeks.

Results for the operation

More requests resolved, with less risk and more visibility.

More resolution, shorter queues. Requests that cross several departments are handled end to end, without handing the customer from team to team.

Control before any action. Every operation goes through risk rules, identity checks and, when needed, human approval before touching your systems.

Visibility and cost under control. Every interaction leaves an auditable record, and the operation tracks outcome, deadlines and AI cost per interaction.

How it works

From request to result in five steps.

  1. Understands the request

    Identifies what the customer wants and which areas it touches, using objective rules first and AI only when needed.

  2. Routes to the right agent

    Calls the agent for each area and, when a request crosses several, coordinates the tasks in the right order and combines everything into one answer.

  3. Checks the risk

    Before every action, checks permissions, customer identity, limits and history. The result is to allow, ask for verification, ask for approval or deny.

  4. Acts and replies

    Carries out the task in the company's systems exactly once and informs the customer. If an approval is pending, the customer is told when it is decided.

  5. Records and measures

    Keeps the audit trail, the cost and the outcome of every interaction, so the operation can track and improve.

An example

A telecom operation, from request to compensation.

Illustrative

A fictional customer of a telecom operator: “My internet went down and I want compensation.” The request crosses three areas. The same flow applies to any industry, such as an insurance claim or a bank dispute.

Step Who acts
Understands the request and identifies network, billing and customer care Hypervisor
Confirms the outage and the time without service Network agent
Calculates the credit owed on the invoice Billing agent
Assesses risk and asks for approval because it is a credit Risk control
Reviews the action card and approves Supervisor
Applies the credit and tells the customer in the conversation Hypervisor

The whole path is recorded: who asked, what was decided, who approved and what was done. For small amounts the policy may waive approval, and for large amounts it may require two people.

A platform with no industry

One platform, any operation.

  • One engine for everyone

    Understand, route, assess risk, approve, execute and audit. The engine does not know what an invoice, a policy or a complaint is, which is why it serves any area.

  • Your operation on top

    The company brings its agents, risk rules and limits, the systems the AI may call and its case types. All of it is configured, without changing the engine.

  • Change without a new release

    Agents, rules and flows change through configuration, with no new development, and versions are recorded.

  • Each company isolated

    Each company's agents, tools, cases and data are kept separate, so very different operations can run on the same platform.

For the teams

Those who operate can see and decide.

  • Case dashboard

    A queue of cases with status, customer and the full timeline of each interaction.

  • Approvals with context

    The approver sees a card with the operation, amounts, customer, verification level and the risk control's decision, and can adjust the values allowed.

  • Grouped cases and deadlines

    An event affecting many customers, such as a mass outage, becomes a single case with deadlines, alerts and indicators.

  • Business metrics

    Interactions resolved without human intervention, those waiting for a person, risk control decisions and AI cost per period.

For the IT team

Integrates with what you already have.

  • Your systems, through APIs

    Agents call the company's systems through APIs, with credentials in a secrets vault and allowed domains set per company.

  • AI providers of your choice

    Anthropic, OpenAI and Google, switchable by configuration, with cost control per execution.

  • Channels and events

    Chat, app, WhatsApp, voice and API. Results come back through signed webhooks, with delivery retries and a versioned contract.

  • Production-ready

    Per-company isolation, corporate identity (OIDC), observability, delivery reconciliation and container-based deployment.

Who it is for

Built for those accountable for operations and technology.

  • Operations leadership

    More resolution without growing the team, with visibility of deadlines, approvals and cost.

  • IT leadership

    Integration with existing systems through APIs, with security, isolation and configuration without new releases.

  • Risk and compliance

    Explicit rules, human approval and an audit trail that cannot change without leaving a trace.

  • Customer care and experience

    Answers that resolve instead of redirecting, in chat, app, WhatsApp or voice.

Trust and control

AI acts within the rules your company sets.

  • Risk decision before acting

    Every action has a risk class. The company's policy sets value and frequency limits, and the result is to allow, ask for verification or approval, or deny.

  • Tamper-evident auditing

    Every event sits in a hash-chained record that can be verified at any time. Nothing changes without leaving a trace.

  • Identity and privacy

    The customer is identified by the channel and never by the AI. Personal data is protected, with retention, deletion and legal hold. Voice does not store audio.

  • Human in the loop

    Sensitive operations wait for approval, including dual approval, and the AI never denies on its own based on a score.

  • Cost and execution control

    Cost limit per execution, safe repetition of writes, cancellation and recovery of stuck executions.

Before and after

What changes in the operation.

Chatbot and manual queuesWith Hypervisor
Answers questions and hands off the restResolves the request and executes the task in the systems
The customer moves from team to teamA single interaction coordinates all areas
Rules scattered and hard to auditCentralized risk rules, with versions and history
Every change requires developmentAdjustments by configuration, with no new release
Little visibility into what the AI didFull trail of every decision, approval and cost

Rollout

From pilot to operation, in phases.

  1. Discovery

    We map the operation, systems and risk rules, and choose the first flows.

  2. Read-only pilot

    Agents look up and answer without changing anything in the systems, to validate quality.

  3. Actions with approval

    Write operations come in, under limits and with human approval.

  4. Expansion

    New flows, areas and channels are added through configuration, on the same platform.

Any line of business

Telecom is one example. The platform has no industry.

Hypervisor was designed not to depend on any industry. Telecom, banking, insurance, energy and water, healthcare, retail and the public sector are all areas where requests cross departments and need control, and all of them are built on the same engine. Want to see it applied to your operation? Request a demo.

Frequently asked questions

What operations and IT leaders ask.

Can the AI make mistakes?

Yes. That is why no sensitive action depends on the AI alone: it goes through risk rules, limits and, when needed, human approval, and everything is recorded for review.

Who is accountable for a decision?

The company sets the rules and who approves. The platform records who asked, what was decided, who approved and what was done, in an audit that cannot be altered without leaving a trace.

Do I need to replace my systems?

No. Agents use the APIs your company already has, and your systems remain the source of truth.

Does my data leave the company?

Data is isolated per company, personal data is protected, retention and deletion are configurable and credentials stay in a secrets vault. We discuss the deployment model in the demo.

Does it work in my industry?

The platform does not depend on an industry. You bring the agents, rules and systems of your area, and the engine is the same.

How long does it take to start?

It depends on the flows and integrations. The path is phased, starting with a read-only pilot, and timelines are set during discovery.

Which channels are supported?

Chat, app, WhatsApp, voice and API integration. Each channel has its own identity and permissions.

See Hypervisor

Put AI agents to work, with control from end to end.

Talk to Karpa AI about how Hypervisor applies to your operation, whatever your industry.

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