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AI-native fraud and AML platform with real-time decisioning and cross-entity intelligence for banks, fintechs and payments.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
Developer framework and LlamaParse service for parsing documents and building AI agents and RAG workflows over them.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦Real-time AI fraud/AML decisioning
- ✦Adaptive ML detection engine
- ✦Cross-entity link analysis
- ✦AI agents incl. conversational 'Vera'
- ✦Investigation and reporting tools
- ✦Low-latency scoring at high QPS
- ✦Smart data annotation with SAM-powered one-click masks across six task types
- ✦Cloud training with 22+ GPU configurations from RTX 2000 Ada to B200
- ✦Support for YOLOv5 through YOLO26 model families
- ✦One-click deployment across 43 global regions with auto-scaling
- ✦Export to 18 formats including ONNX, TensorRT, and CoreML
- ✦Live training metrics and experiment comparison dashboard
- ✦Real-time AI answers during technical interviews
- ✦Invisible to screen sharing and recording
- ✦Hidden from dock, tray and activity monitor
- ✦Click-through overlay
- ✦Live audio capture and transcription
- ✦Lifetime unlimited access license
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- ✦LlamaParse document parsing and extraction
- ✦Open-source framework for AI agents and workflows
- ✦Document indexing for retrieval/RAG
- ✦Prebuilt solutions by industry and use case
- ✦Free starter credits for LlamaParse
- →Stop payment, card and check fraud
- →Prevent account takeover and application fraud
- →Meet AML/BSA compliance
- →Onboard customers with less friction
- →Building and training custom object detection or segmentation models
- →Labeling large image/video datasets for computer vision projects
- →Deploying vision models to edge or mobile devices
- →Running quality control or defect detection in manufacturing
- →Powering retail, logistics, or agriculture vision applications
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Parse complex documents for AI apps
- →Build RAG and agent workflows
- →Automate invoice and claims processing
- →Search across technical documents