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Multimodal & Computer-Use AI

AI across screens, images, voice, and video

Let AI work with the formats your business actually runs on

Enterprise work is not confined to clean text. It lives in invoices, drawings, photographs, calls, videos, scanned forms, dashboards, and interfaces that were never designed for APIs. Multimodal AI can interpret those formats together; computer-use agents can navigate a screen when no safer integration exists. Altivate turns both capabilities into controlled workflows—not unattended clicks.

A multimodal observe-reason-act loop.

  1. Observe: Documents, images, audio, video, screens, and sensors
  2. Understand: Extract entities, conditions, intent, and uncertainty
  3. Decide: Apply business rules, context, and human authority
  4. Act: Use APIs first; controlled interface actions when required

Outcome: Unstructured signals converted into traceable enterprise work

A MULTIMODAL OBSERVE-REASON-ACT LOOP01ObserveDocuments, images, audio,video, screens, and sensors02UnderstandExtract entities, conditions,intent, and uncertainty03DecideApply business rules,context, and human authority04ActUse APIs first; controlledinterface actions whenrequiredUnstructured signals converted into traceable enterprise work
A multimodal observe-reason-act loop.
Capability

One reasoning layer across multiple modes

The value comes from connecting perception to a business process, not from describing an image in isolation.

Document understanding

Read layouts, tables, handwriting, stamps, signatures, diagrams, and attachments while preserving page-level evidence and confidence.

Vision-language operations

Combine visual inspection with work orders, specifications, asset history, and quality rules to identify what matters and what happens next.

Voice and conversation intelligence

Transcribe, summarize, classify intent, detect required actions, and connect a conversation to customer, service, or case context.

Video and event understanding

Find relevant moments, track conditions over time, and create searchable operational evidence without asking people to watch every frame.

Computer-use automation

Operate browser, desktop, or mobile interfaces through screenshots and controlled actions when a dependable API is unavailable.

Cross-modal verification

Compare a delivered item with a purchase order, a site photograph with a drawing, or a recorded interaction with the resulting transaction.

Safe delivery

Design computer-use agents as constrained operators

Interface automation has a larger attack and error surface than a typed API, so the control model must be explicit.

01

Prefer stable system interfaces

Use approved APIs, events, and workflow services wherever possible. Reserve screen operation for the narrow gaps that cannot be integrated safely another way.

02

Constrain the environment

Limit domains, applications, accounts, data, action types, and session lifetime. Run in isolated environments with secrets kept outside screenshots and prompts.

03

Verify before consequence

Require confirmation for irreversible, financial, sensitive, or externally visible actions and show the exact proposed change before approval.

04

Record and replay

Capture observations, chosen actions, outcomes, failures, and screenshots needed for audit while applying retention and privacy controls.

Control boundary

Choose the safest execution path

Visual interaction is valuable, but it should not replace a stronger integration simply because it is easier to demo.

PathUse it whenKey controls
API or eventThe system exposes a stable, supported interface.Typed inputs, least privilege, idempotency, audit
Workflow automationBusiness rules and approvals span known systems and people.State machine, approvals, retries, exception ownership
Computer useA critical legacy or external interface has no viable integration.Isolated session, allowlists, visual checks, human confirmation
Human-onlyThe action is too ambiguous, sensitive, or irreversible for safe automation.AI may prepare evidence, but a person decides and acts
Use cases

Multimodal workflows with a measurable operational result

Each case connects perception to a transaction, exception, or decision.

Intelligent document operations

Extract and reconcile invoices, delivery notes, contracts, certificates, and forms before posting structured data or routing an exception.

Visual quality and safety

Compare images or video with specifications and operating rules, then create evidence-backed defects, work orders, or review tasks.

Field service assistance

Interpret equipment photographs, labels, readings, and technician voice notes alongside manuals, parts, and asset history.

Legacy process completion

Navigate a narrow, repetitive interface task under strict session limits while a person approves consequential changes.

Questions

Multimodal and computer-use AI FAQ

Is computer-use AI the same as robotic process automation?

They overlap, but computer-use models interpret visual state and adapt actions dynamically, while traditional RPA follows more deterministic selectors and rules. Many reliable solutions combine both.

Can multimodal AI replace document templates?

It can reduce template dependence, but critical fields still need validation, confidence thresholds, business rules, and human review when the source is ambiguous or the consequence is high.

How do we protect sensitive information in screenshots and recordings?

Use isolated sessions, masking or redaction, least-privilege accounts, controlled retention, encrypted storage, and policies that keep credentials and unrelated personal data out of model context.

Continue exploring

Related AI capabilities

Embedded delivery

Turn one document, visual, or legacy workflow into working AI

Altivate’s Forward Deployed AI Engineers test the real inputs, systems, failure modes, and approvals with your team—then ship the smallest safe workflow that changes the operating result.

Sources, proof and authorship

Sources for multimodal and computer-use AI

Use these sources to inspect the underlying guidance, published customer evidence and named analysis. Adjacent proof is labelled explicitly.

Interested?

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