Vision AI models
Vision AI models, built for your data & workflows
VLMs for visual understanding, backed by LLMs, voice, SLMs, and edge models. Designed, fine-tuned, and owned by you.
Key benefits
Domain accuracy via SFT
Supervised fine-tuning on your terminology, databases, and history. Fewer hallucinations.
Enterprise security & compliance
Full data isolation in your VPC or data center.
Flexible multimodal architecture
LLMs for deep text reasoning, VLMs for visual understanding, & voice models for conversational AI.
Optimized latency & compute
Custom sizing, quantization, and edge deployment tuned to your SLAs.
How it works
Your application layer
- Web apps
- Internal tools
- Edge devices
- API
VisionX vision AI model
LLMText and reasoningVLMVisual understanding · document readingVoiceConversationalBuilt with SFT · Quantization (vLLM / TensorRT) · RAG vector DB
Deployment and infrastructure
- AWS
- Azure
- GCP
- Edge devices
- On-premises
- Private cloud
Deployment methodology
Assess data quality, decide LLM / VLM / Voice / SLM / Edge on latency & cost, set baseline eval metrics.
Private data pipelines, supervised fine-tuning on baseline architectures, functional PoC.
Quantize for inference speed, run red-team safety evals, integrate your API / Edge layer.
Deploy to your infra or edge hardware, set up drift monitoring, train your engineering team.
Deploy and own
Edge
On device, low latency
On-premises
Air-gapped. Your GPUs
Cloud
Your VPC / your account
How we engage
Start with a 90-day validation. Grow at your own pace, one proven step at a time.
See the full model- Validate
- Run
- License
- Own