Multimodal AI
Multimodal AI development services
Text, image, audio and video, understood and generated together.
In one paragraph
Multimodal AI services build systems that work across text, images, audio and video: text-to-image and image-to-text, video understanding and generation, audio AI, vision-language applications, AI avatars and animation. Marketing, e-commerce, media, training and support teams use them to create content at scale, understand visual and spoken input, and offer richer product experiences.
Why it pays off
- Content production time and cost cut dramatically
- Consistent brand output with human approval
- New product experiences across image, voice and video
- Rights, consent and disclosure handled by design
- Pipelines that scale beyond one-off generations
What's included
Multimodal AI: everything in this service
Text-to-image generation
On-brand image generation pipelines for products, campaigns and content, with style control and approval flows.
Image-to-text & captioning
Describe, tag, caption and extract structured data from images at scale for catalogues, accessibility and search.
Video understanding AI
Transcribe, summarise, search and moderate video; detect scenes, objects and events.
Audio AI
Speech, music and sound understanding and generation: transcription, dubbing, voice, sound classification.
Vision-language systems
Applications that reason over images and text together: visual QA, document understanding, product assistants.
AI video generation
Generate and edit short-form, explainer and product videos from scripts, images and templates.
AI animation
Motion, character and scene animation pipelines that cut production time for creative teams.
Multimodal assistants
Assistants that accept photos, voice and documents and reply with text, images or speech.
AI dubbing & localisation
Translate and re-voice video and audio content while preserving timing and speaker identity.
Generative media pipelines
Batch generation, review, versioning and rights tracking for large volumes of AI-created media.
Use cases
Where it creates value
Product content at scale
Generate and caption product imagery and descriptions for large catalogues, on brand and reviewed.
Training and explainer video
Produce and localise instructional video with avatars and AI voices in days rather than weeks.
Visual support
Customers send a photo; the assistant identifies the product or issue and responds appropriately.
Media search and moderation
Search and moderate large image and video libraries by content, not filenames.
Personalised video
Individualised video messages for sales, onboarding and customer success.
How we deliver
How we deliver multimodal ai
- 01
Use-case and rights review
Define the outputs, brand rules, consent and licensing requirements, and how humans will review.
- 02
Model and pipeline selection
Test image, video, audio and vision-language models on your material for quality, cost and speed.
- 03
Pipeline build
Prompt templates, style controls, generation, editing, review and asset management integrated with your tools.
- 04
Quality and safety checks
Automated checks for brand, safety and rights, plus human approval where outputs go public.
- 05
Scale and operate
Batch workflows, monitoring and cost tracking as volume grows.
Frequently asked
Multimodal AI: questions we get
Generally yes when produced with models and services whose licences permit commercial use, and when you avoid reproducing protected characters, logos or real people without consent. We document the tools and terms used, add rights tracking to the pipeline and recommend human review before publication. For high-visibility campaigns we can also run similarity checks against known works and keep a record of prompts and seeds for each asset.
Style references, fine-tuned or LoRA-adapted models on your assets, controlled prompt templates, negative prompts and automated brand checks, followed by an approval step. Consistency improves with a small library of approved examples. Where the brand has strict guidelines we encode them as automated checks (colours, composition, prohibited elements) that run before anything reaches a reviewer.
Only with their documented consent, and with disclosure to viewers where required. We build consent, usage limits and revocation into the process, and can watermark outputs. For most training and marketing needs a licensed stock or synthetic avatar is simpler. Where you do use a real person, we keep the consent record, the voice sample and the permitted uses together with the asset so it can be honoured later.
AI voices, translation and lip-sync now support many languages, so one video can be localised into several with review. We check pronunciation of names and terms and keep a glossary per language. A native speaker reviews the first videos in each language, and their corrections become rules for later batches.
Automated checks for artefacts, safety and brand rules, sampling for human review, versioning of every asset and a feedback loop that adjusts prompts and models. Nothing goes public without the level of review you set. Review effort typically falls over the first weeks as prompts and checks are tuned, so the pipeline gets cheaper as it scales.
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