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Build. Deploy. Monitor. Your VPC-first backend for AI and computer vision — shipped with APIs, jobs, data, and observability so you can launch fast and own it all.
Launch fast with production templates for auth, APIs, storage, and events
Scale from prototype to production without cost surprises
Secure by default with secrets, roles, and audit logs
Built for AI and computer vision with model-chaining and foundation-model adapters
A visual way to design pipelines that chain models, classic CV ops, and business rules. We can integrate a best-of-breed editor or ship a tailored builder in your repo. Supports condition/expression style logic and sinks like S3, webhooks, and alerts.
Detection/segmentation/classification, classical CV steps, OCR/VLMs, post-processing, and publish/alert actions. Bring your own models or wire to hosted endpoints.
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Uploads, REST, webhooks, RTSP/video streams, and batch jobs. Outputs to APIs, queues, databases, S3, and downstream apps.
Built-in logs, metrics, and alerts for pipeline health. Supports integration with tools like Grafana.
![[background image] image of a modern office space (for a ai healthcare company)](https://cdn.prod.website-files.com/68994a54b8ff4d8dcf5998ec/68b7d872d588d8e0fcca3961_envato-labs-ai-480d132c-43aa-4af3-b033-36e44ef248e6.jpg)
Real-world AI, web apps, and 3D—crafted for startups, educators, and enterprise teams. Explore our latest projects below.
Ship as a managed API in your cloud or as Docker containers for on-prem/edge devices; internet optional. We design once and deploy anywhere, including GPU nodes where needed.
Chain multiple models in one pipeline and tap foundation models where it helps. Keep data in your VPC.
Process large image/video sets with batch jobs or respond to live events and streams.
From monitoring metrics to resolving edge cases and rolling out new features, we give you the tools to keep your systems reliable, adaptable, and continuously improving
Dashboards for latency, throughput, costs, and model outcomes, plus alerts for failures and regressions.
Queue edge cases for review and route feedback back to training datasets or labeling tools.
A B rollout for models and features. Shadow tests and canaries before full release
![[interface] screenshot of core features (for an ai developer tools)](https://cdn.prod.website-files.com/68994a54b8ff4d8dcf5998ec/68b7d87d8ee1a2e67b176599_envato-labs-ai-6ae3e38d-afc2-402a-a95f-9ea25acf0db4.jpg)
One interface for hosted endpoints or your own containers
Cloud API or edge builds for devices and on prem
Feature flags and gradual rollout with automatic fallbacks
Goals, constraints, success metrics
System design, data model, cost plan
Templates + pipelines wired to your use cases
Cutover plan, dashboards, alerts
Docs, training, and optional managed SRE
What powers our builds? Dive into the tools, frameworks, and AI magic behind every Lid Vizion project.
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