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Enterprise conversational-AI suite from FPT for chatbots, voice agents, eKYC and document automation across industries.
Enterprise Work AI platform for company-wide search, an AI assistant and building governed agents across 250+ connectors.
ByteDance's Coze (Kouzi): an all-in-one AI office assistant for writing, slides, sheets, design, podcasts and images.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
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- ✦Chatbot and conversational-AI building platform (Chat/Engage)
- ✦AI voice agents and text-to-speech (Voice Maker)
- ✦eKYC identity verification
- ✦Document reading and automation (FPT AI Read)
- ✦AI agents for customer service and knowledge management
- ✦Industry solutions for banking, insurance, retail, logistics
- ✦Enterprise search across company apps
- ✦Personal AI assistant grounded in work data
- ✦Agent builder, orchestration and governance
- ✦250+ connectors and actions
- ✦Enterprise knowledge graph and hybrid search
- ✦Security controls for scaling AI
- ✦AI writing
- ✦AI presentation/PPT generation
- ✦AI spreadsheets and tables
- ✦AI design
- ✦AI podcast generation
- ✦AI image generation
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- →Automating customer service with chatbots and voice agents
- →Verifying identity with eKYC during onboarding
- →Automating document processing
- →Improving call-center quality and sales efficiency
- →Search across all company knowledge
- →Answer employee questions with grounded AI
- →Build and deploy custom AI agents
- →Automate cross-system workflows
- →Drafting documents
- →Building presentations
- →Generating spreadsheets
- →Creating designs and images
- →Producing podcasts
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects