Multi-modal Agents
AI that sees, reads and acts. We build agents using Gemini, GPT and Claude that process images, documents and interfaces to complete real work.
Beyond text-only AI
Modern AI models process multiple input types natively. Multi-modal agents combine these capabilities to handle tasks that require seeing, reading and understanding context.
Image understanding
Agents that interpret screenshots, photographs, diagrams and charts to extract information or make decisions based on visual content.
Document processing
Reading and understanding PDFs, forms, invoices and other structured documents without manual template configuration.
Computer use
Agents that interact with graphical interfaces, navigating web applications and desktop software to complete tasks.
Why multi-modal matters
Most business processes involve more than text. Multi-modal agents work with information in the form it actually takes.
Native understanding
Models like Gemini and GPT process images and documents natively rather than relying on separate OCR or vision pipelines.
Reduced preprocessing
Send documents and images directly to the model instead of building complex extraction pipelines as an intermediary step.
Richer context
Agents that see layout, formatting and visual cues understand documents better than text-only approaches.
Interface automation
Computer use capabilities allow agents to interact with legacy systems that lack APIs, using the same interfaces humans use.
Model flexibility
Choose the right model for each modality. Gemini excels at video, Claude at computer use, GPT at broad vision tasks.
End-to-end workflows
Combine vision, text and action in single agent workflows rather than stitching together separate single-purpose tools.
Use cases for multi-modal agents
Document extraction
Processing invoices, contracts, receipts and forms by understanding layout and content together.
Quality inspection
Visual inspection of products, materials or environments using image analysis and defect detection.
Legacy system automation
Agents that interact with older applications through their user interfaces when APIs are unavailable.
Content moderation
Reviewing images, videos and text together for policy compliance and content safety at scale.
Insurance claims
Processing claim documents, damage photographs and supporting evidence in a single automated workflow.
Accessibility
Describing images, interpreting charts and making visual content accessible through natural language.
Model options
We select the right model for each modality and task, combining capabilities from multiple providers where needed.
Google Gemini
Natively multimodal with strong video and image understanding. Excellent for document processing.
OpenAI GPT
Broad vision capabilities with strong general-purpose image understanding and generation.
Anthropic Claude
Computer use capabilities for interface automation alongside strong document understanding.
Frequently Asked Questions
Which model is best for multi-modal tasks?
It depends on the specific modality and task. Gemini is strong for video and native multimodal understanding, Claude excels at computer use, and GPT offers broad vision capabilities. We help you choose the right fit.
How reliable is computer use?
Computer use is improving rapidly but still requires careful guardrails, human oversight and well-defined task boundaries. We design systems with appropriate safety controls.
Can multi-modal agents replace our OCR pipeline?
In many cases yes. Native document understanding is often more accurate and flexible than traditional OCR, especially for varied document formats and layouts.
What about cost for image and video processing?
Multi-modal inputs cost more per token than text. We design architectures that use vision capabilities selectively and efficiently to manage costs.
Build multi-modal agents
We help organisations build AI agents that work with images, documents and interfaces. Book a call to discuss your requirements.