Enterprise AI Agent &
Multimodal Workflow Platform

Let AI do more than answer questions. It understands needs, plans steps, calls tools, executes processes, and orchestrates complete business systems.

Line illustration of an AI Agent multimodal workflow
1 AI Brain
4 Use Cases
5 Capabilities
7 Infrastructure

One Unified Architecture

Four business scenarios sharing the same AI brain

AI Brain architecture diagram

Four Core Use Cases

Covering the most common enterprise AI-native workflow needs

AI-assisted Coding (Vibe Coding)

  • Code writing / packages / debugging
  • API, SQL, and script generation
  • Support and DevOps automation

AI Agent Workflows

  • Autonomous step planning
  • Tool calling and multi-system collaboration
  • Complete business outcome delivery

Security + AI

  • Code risk detection
  • Prompt injection and sensitive data detection
  • Audit, compliance, and log analysis

Image / Video Production

  • Script and storyboard generation
  • Prompt and multimodal control
  • Image / video model content generation

Five Core Capabilities

Reasoning

Understand complex needs and form judgments and strategies

Planning

Break down tasks into executable steps

Orchestration

Coordinate models, tools, data, and systems

Memory

Preserve context, state, and history

Routing

Select the right models and workflows for each task

Seven Infrastructure Capabilities

Foundational capabilities for enterprise AI Agents and multimodal workflows

Application and Access Layer

Inference APIs

Bedrock / Claude API

Orchestration

Step Functions / Lambda

Queues

SQS / EventBridge

Capability Services Layer

Storage

S3 / RDS / DynamoDB

Analytics & Monitoring

CloudWatch / Athena

Data and Infrastructure Layer

Vector Search

OpenSearch / Bedrock KB

Multi-region Infra

Route53 / Global Accelerator

Move AI from Conversation to Execution

Build a truly reliable
Enterprise AI Agent & Multimodal Workflow Platform