WISIO
WISIO Studio

Every Tool to Annotate, Train, and Deploy Vision AI

AI-assisted annotation, no-code model training, real-time inference, and cloud-to-edge deployment — all in one platform.
Feature 01

Advanced Annotation Engine

Empower your team with a highly responsive, AI-assisted annotation canvas that speeds up labeling while maintaining pixel-perfect accuracy.

AI Auto-Label
Edge Detection
Multi-Format
Collaborative
QA Features

conveyor_run_0117.jpg

Feature 02

Seamless Machine Learning Pipelines

From data ingestion to model deployment, track every step of your machine learning lifecycle with comprehensive visual metrics and control.

End-to-End
Training Automation
Experiment Tracking
Versioning
Monitoring
Data Prep30%
Training80%
Evaluation45%
Deployment100%
Feature 03

AI Document Extraction

Extract structured data from invoices, forms, and documents automatically. Our AI models convert visual documents into clean JSON with no manual parsing.

Invoice OCR
Receipt Parsing
JSON Output
Auto-Field Detection
Audit-Ready

AWS

AMAZON WEB SERVICES

Tax Invoice · INV-2026-001

Vendor

Amazon Web Services HK

Invoice #

INV-2026-001

Date

20/04/2026

Amount

HK$420.15

Account

6500 · Cloud Services

AI Confidence

97.8%

INV-2026-001-AWS

extraction_output.json

{
  "invoice_id": "INV-20▇

AI extraction complete

Feature 04

Agent Zero Intelligence

Interact with your entire ecosystem using natural language. Agent Zero answers questions about your workspace, models, datasets, and training results.

Natural Language
Workspace Context
Labelling Advice
Platform Help

Agent Zero

3 Datasets
2 Models

What was my best model this month?

Ask about your workspace...

?

Feature 05

Frictionless Edge Deployment

Push trained models securely to edge devices. Monitor health, performance, and apply updates entirely over-the-air from the cloud.

RTSP/HTTP
Real-time Inference
Multi-Camera
OTA Updates
Offline

detect-v2.onnx

7.2 MB · INT8

WISIO Cloud

47 ms

Edge Node

Latency:

47 ms

Bandwidth:

Offline-OK

OTA Sync:

Queued

Feature 06

Unified Camera Management

Based on live video streams, apply AI models, trigger alerts, and run real-time inference natively on streaming feeds.

Live AI Inference
Alert Triggers
Edge Sync
Multi-Stream
No-Code

WISIO Camera Grid — 4 feeds active

1 ALERT

CAM-01

Person · 97%

CAM-02

Vehicle · 94%

CAM-03

Zone Breach!

CAM-04

Forklift · 91%

Flexible Deployment Options

Run WISIO where your data lives — cloud, API, on-premise, or edge.

WISIO Studio
Cloud SaaS

Full-featured cloud platform. Annotate, train, deploy, and monitor — all in one browser-based workspace.

REST API
Developer

Integrate inference and management directly into your stack. API-documented, JWT-secured endpoints.

WISIO Go
Mobile Edge

Lightweight mobile & tablet client for field inspection teams. Runs models locally with offline support.

WISIO Nexus
On-Premise

Self-hosted on-premise deployment for air-gapped or high-compliance environments. Supports local deployment and offline inference.

Frequently Asked Questions

What annotation tools does WISIO provide?
WISIO includes bounding box, polygon, semantic segmentation, keypoint, and AI-assisted smart auto-labeling tools. The annotation engine uses existing model predictions to pre-fill labels, which human annotators then review and correct — significantly reducing manual effort.
Which model architectures are supported for training?
WISIO supports object detection, instance segmentation, image classification, and anomaly detection. Multiple real-time detection and transformer-based segmentation architectures are available. Anomaly detection uses a separate unsupervised pipeline based on patchcore and similar approaches.
How does the auto-labeling workflow work?
Upload a pre-trained or in-progress model, select a batch of unlabeled images, and WISIO automatically runs inference to generate label candidates. Reviewers accept, correct, or reject each prediction before committing it to the dataset.
Can I export models in ONNX or TensorRT format?
Yes. After training, WISIO supports model export to ONNX, TensorRT, and CoreML formats, enabling deployment to any runtime that supports these standards — including edge devices, custom inference servers, and mobile applications.
What integrations and APIs are available?
WISIO exposes a REST API documented with OpenAPI/Swagger, covering dataset management, model inference, and application lifecycle operations. JWT-based authentication, webhook support, and SDK examples are all built in.
How does active learning reduce annotation effort?
WISIO identifies images where the current model has the highest prediction uncertainty. Annotating these high-uncertainty samples first improves the model faster than random sampling — typically reducing total annotation effort by 40–60% to reach the same accuracy target.